Senior Data Scientist Resume Samples

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AK
A Kessler
Anissa
Kessler
35425 Block Burg
Philadelphia
PA
+1 (555) 920 9128
35425 Block Burg
Philadelphia
PA
Phone
p +1 (555) 920 9128
Experience Experience
San Francisco, CA
Senior Data Scientist
San Francisco, CA
Steuber, Schmidt and Stark
San Francisco, CA
Senior Data Scientist
  • Work with a range of proprietary, industry standard, and open source data stores to assemble and organize and analyze data
  • Stakeholder management
  • Bring in quality/process improvement expertise in the realm of data science
  • Providing thought leadership in statistics and data analysis to the entire analytics organization
  • Automating models and metrics that track product performance
  • Working independently, develop prototype concepts and manage experiments to create data-driven solutions to business problems
  • Providing real-time business analytics and visualization for Internal customers
present
Chicago, IL
Senior Data Scientist
Chicago, IL
Batz, Mertz and Kuphal
present
Chicago, IL
Senior Data Scientist
present
  • To help develop and support the use of the Analytics Centre of Excellence policies, tools, and best practices across the enterprise
  • To help develop proposals and feasibility studies for small to medium projects
  • Working with the academic and business community to develop new techniques and to contribute to research in the area of advanced analytics on large databases
  • Identifying opportunities for improvement in data cleansing, manipulating, and processing within existing software applications and frameworks
  • Develop and maintain strong relationships with Power Users, Project Managers, Business Systems Analysts, and ETL Developers
  • Create and contribute relevant content and materials to the Analytics CoE
  • Query development
Education Education
Bachelor’s Degree in Computer Science
Bachelor’s Degree in Computer Science
University of Central Florida
Bachelor’s Degree in Computer Science
Skills Skills
  • Highly motivated self-starter with experience producing high quality data deliverables and able to work independently and in a team environment
  • Highly proficient with one or more data mining / predictive modeling tools such as SAS, JMP, Python, R, as well as proficient in SQL
  • Strong written and oral communication skills. Expertise in Microsoft PowerPoint, excel, Outlook and Word, Power BI/Tableau/other visualization capability
  • Solid analytical problem solving with strong attention to detail and an obsession with data accuracy
  • Strong oral and written communication skills and be able to communicate complex technical knowledge in layman’s terms
  • Strong data & visual presentation skills and ability to explain insights using tools like tableau, D3 charts or other tools
  • Excellent project management, planning and organizational skills; ability to multi-task in order to move forward in highly dynamic situations
  • Great communication skills and able to guide developers that may not have your depth of data science ability
  • Use strong business, problem solving skills and programming knowledge to quickly cycle hypotheses through discovery
  • Personable and likeable – able to connect with a broad spectrum of individuals
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15 Senior Data Scientist resume templates

1

Senior Data Scientist Resume Examples & Samples

  • To support the influence and impact across the enterprise in promoting the analytics strategic direction across the enterprise
  • Provide consulting services to our EIM business partners on their information consumption and analytical needs
  • Participate in Proof of Concept or Proof of Technology projects
  • Provide expertise & training to business users
  • To help develop proposals and feasibility studies for small to medium projects
  • Conduct technology research, evaluate Analytics tools and produce strategy/direction papers
  • Develop and maintain strong relationships with Power Users, Project Managers, Business Systems Analysts, and ETL Developers
  • Create and contribute relevant content and materials to the Analytics CoE
  • 2 years of work experience with Analytics technologies: Aster, SAS, Hadoop, Hive, Pig
  • Strong knowledge of design, development, and implementation experience in an Enterprise Data Warehouse Environment utilizing current Analytics technologies
  • Very strong interpersonal and communication skills (both written and oral); ability to communicate with people in a wide variety of areas and at various levels from technical specialists to senior executives
  • Must have some knowledge in Analytics technology integration and architecture
  • Must be able to work in a high functioning team environment
  • Knowledge of Data Warehouse concepts and methodologies and their practical application in a production environment
  • Knowledge of Relational database concepts and design
  • Knowledge or experience in the Financial or Insurance industry is preferred
2

Senior Data Scientist Resume Examples & Samples

  • B.S. or M.S. degree in quantitative or CS fields, and 8+ years of progressive experience in decision support, analytics, or related field
  • 5+ years applied, recent experience with a RDBMS platform, such as Oracle, DB2, or SQL Server. Applied experience with distributed, column store platforms such as Vertica or Greenplum a strong plus
  • 5+ years applying scripting languages to text and data manipulation, such as Ruby, Python, Perl, or shell scripting
  • Working knowledge of Map-Reduce, Hive, Pig, R. Desirable: Perl, C/C++, and/or Java
  • Demonstrated hands on experience applying complex SQL to solve analytic problems
  • Familiar with database design, marketing automation, web analytics, and internet marketing data systems demonstrated ability to build effective data models to support analysis
  • Thorough understanding of internet marketing data collection and metrics experience with a recurring revenue business model
  • Prior experience with experimental design, statistical data analysis or model creation on big data a plus
  • Excellent written and spoken communication skills experience working with and supporting less technical analysts able to work with technical IT resources
  • Demonstrated capacity to learn, intellectual honesty and independent thinking. Must be comfortable with unstructured, fast-moving and constantly evolving high growth environment. Passion for excellence and continuous self-driven improvement
3

Senior Data Scientist Resume Examples & Samples

  • Research, develop and implement new methods of measuring and analyzing data sets and processes
  • Work with a range of proprietary, industry standard, and open source data stores to assemble and organize and analyze data
  • Design models to answer targeted business questions and engage in data analysis at the highest level
  • Educate other analysts and business team members to expand impact to additional products or business units
  • Construct and present research ideas, prototypes and proofs of concepts
  • Experience with mapping business needs to engineering systems
  • Fluent in modern advanced analytical tools (e.g. Python, R, MATLAB etc.)
  • Substantial experience with the use of relational databases for data storage and analysis including fluency with using SQL for data extraction and management (MSSQL, Oracle, MySQL, postgresql etc.)
  • Knowledge of NoSQL data stores, MapReduce and software frameworks like Hadoop
  • Must be able to address multiple priorities in an extremely fast-paced environment."
4

Senior Data Scientist Resume Examples & Samples

  • Aggregate and analyze data to create actionable insights on Chase’s customers to increase customer acquisition, loyalty, cross-sell, and to develop new forms of ROI across the business
  • Use advanced analytical techniques to segment our customers into actionable segments/micro-segments enabling more holistic customer strategy and experience
  • Collaborate with strategic partners (customer segmentation team, LOB marketing, digital services) to identify and recommend unique customer experiences across segments and channels
  • Use customer value/profitability measures to further segment and identify lifetime value and ROI based metrics to measure the efficiency of marketing vehicles
  • Masters Degree in statistics, mathematics, marketing, engineering, economics or an applied science
  • 7+ years of hands-on experience leading the development of customer insights leveraging complex statistical methods, experimentation and visual analytics in digital or financial services domain
  • Demonstrable experience driving significant change as it relates to customer segmentation, insights and analytics
  • Expertise in applied statistics, including regression models
  • Experience using statistical software such as R, SAS / SQL or similar tools to analyze, mine and infer business insights
  • Experience with SQL, Hadoop and Greenplum
  • Self-starter who can provide thought leadership and drive results in a dynamic and evolving “big data” environment
  • Developing and communicating business recommendations and insights in easy to understand way leveraging data to tell a story
  • Proficient in MS Word, Excel, Access, and PowerPoint
5

Senior Data Scientist Resume Examples & Samples

  • At the minimum must have a graduate level degree in a quantitative discipline (i.e. Statistics, Applied Mathematics, Operations Research, Industrial Engineering, Computer Science, etc.)
  • Must have 3+ years of experience in applying machine learning techniques to solve business challenges using the following: SQL, R, Python, Apache Mahout, Oxdata H20, Hadoop, etc
  • Must have 3+ years of advanced analytics experience w/ extensive hands-on experience working on analytical studies from: stakeholder interaction, crafting methodology, to data mining/predictive modeling applying leading machine learning techniques using the following technologies: SQL, R, Python, Apache Mahout, Oxdata H20, Hadoop, etc
  • Skilled at translating analysis findings to a non-analytical audience
  • Full time role, No Visa’s, 30/40% travel (domestic and some international) Recruiter: Sunil Sud
6

Senior Data Scientist Resume Examples & Samples

  • Advanced degree in Applied Statistics, Computer Science (Machine Learning), or related field (Masters required, Ph.D. preferred)
  • Experience with advanced data mining and predictive modeling algorithms and techniques for regression, classification, survival modeling, time series, feature selection, etc
  • Experience in statistical inference and analytic techniques
  • Experience with using R for modeling, including developing R scripts
  • Experience with modeling and analysis of large datasets
  • Experience with a scripting language like Python, Perl
  • Strong communication and presentation skills; experience in communicating results of statistical analysis and modeling to a broad audience
7

Senior Data Scientist Resume Examples & Samples

  • 5+ years’ relevant quantitative research and analytics experience
  • Expert knowledge of machine learning and conventional statistical analysis techniques and tools (e.g. R, Python, Stata, etc.) is required
  • Expert proficiency interrogating distributed databases (Map/Reduce, Hadoop, Hive, etc.) is also highly desired
  • Ability to extract and interpret data from various sources to offer creative solutions
  • Graduate degree in a quantitative field: Statistics, Computer Science, Mathematics, Economics, or a related field
  • Extremely strong quantitative and logical problem solving skills and understanding of statistical / machine learning concepts and methodologies
  • Detail-oriented with strong organizational and project management skills, able to work well under deadlines in a changing environment and perform multiple tasks effectively and concurrently
  • Experience working in educational software or educational institutions is highly desirable
  • Excellent written, communication and presentation skills. Comfortable and effective in small group and large group presentations. Compelling and accurate writing ability
  • Experience working with Agile development methodologies
  • Excellent teamwork skills and proven ability to influence cross-functional teams without formal authority
  • Ability to work within a highly dynamic and fast-paced environment
8

Senior Data Scientist Resume Examples & Samples

  • Explore and analyze large medical databases: medical claims, hospital discharges, and/or real-time EMR data feeds
  • Evaluate patients’ current and future risk based on claims and non-claims data
  • Support daily production tasks that require scientists’ involvement
  • Conduct QA of models’ outcomes and regularly monitor model performance
  • Enhance existing predictive models and analytics, and develop new models
  • Develop, implement, and validate new predictive modeling algorithms and applications
  • Build statistical models and complete various analytical projects
  • Provide consultation, training, and analysis to clients, account management and sales staff, and other company personnel
  • Deliver sales presentations and product demonstrations as needed
  • Propose new project and product ideas and provide critical guidance for the development and implementation of models and analytics products
  • Maintain active research and follow industry trends in health risk assessment and analytics in general
  • Publish and/or present novel work in highly regarded journals and meeting forums
  • Work under minimum supervision
  • Serves as a team lead, providing oversight and direction, as well as serve as a team member
  • Ph.D. degree in quantitative discipline: statistics, applied mathematics, computer science, data mining, machine learning, etc
  • Excellent knowledge and thorough understanding of the following statistical techniques and machine learning algorithms: linear and nonlinear regression, logistic regression, classification, cluster analysis, hypothesis testing, decision trees, CART, CHAID, neural nets, SVM, etc
  • 5+ years’ experience in data modeling or comparable work
  • Knowledge of database and proficiency using SQL language
  • Ability to work independently as well as a member of a team
  • Good publication records in peer-reviewed journals and conferences
  • Experience in machine learning, data mining, and/or statistical modeling
  • Experience with handling and modeling large, complex, and “noisy” data
  • Strong knowledge of .Net framework, C# or C++ or Java
  • Familiarity with business intelligence system, dashboard reporting, and analytical reporting
  • Familiarity with techniques of “big data” analytics
  • Clinical or medical knowledge/education
9

Senior Data Scientist Resume Examples & Samples

  • Defines analytic strategies to meet the demands of business requirements
  • Defines the technical requirements of the analytic solutions
  • Defines the data requirements of the analytic solution
  • Designs and/or contributes to the development of a data mining systems that enable reuse, efficiency, manageability and deployment
  • Usually responsible for providing a detailed technical design for enterprise solutions. Is usually the Principal Consultant who analyses and develops enterprise technology solutions
  • Regularly leads large cross functional teams to include technical management of client staff assigned to implementation team in the completion of one or more solution requirements, architecture, or implementation deliverables
  • Provides the technical direction required to resolve complex issues to ensure the on-time delivery of solutions that meet customer expectations. May need to develop new methods to apply to situations
  • Provides advanced technical consulting and advice to proposal efforts, solution design. Provides consulting advice to customer senior leadership and sets strategic direction for customers based on HP's solutions and products
  • Works with peers outside immediate organization to define and characterize complex technology or process problems and/or develops new solutions, yet works independently to drive technical problems to a solution
  • Actively participates in HP professions program and Practice Improvement activities
  • Proactively encourages Re-use within practice or profession
  • Is recognized by peers as an expert in a particular area of technology
  • Sustained and consistent contribution at the region level
  • Experience with Hadoop, Map/Reduce, Hive or equivalent
  • Excellent communication and presentation skills; fluent in English and German
  • Demonstrates ability to develop solutions that can be used at multiple customer sites to enhance the availability, performance, maintainability and agility of their enterprise
  • Develops reusable solutions and workarounds that are innovative and demonstrate a deep technical knowledge of the affected products, processes, and the customer environment. Breadth of knowledge covers additional business units, third parties, competitors, and business drivers
  • May define interoperability issues between vendors' products. Is a recognized expert in one or more technologies across an HP Services (HPS) region. Holds a vendor or industry certification in more than one discipline area. Regularly represents HPS at industry recognized technical events
  • Has performed troubleshooting across a number of significant multi-vendor products
  • Has demonstrated innovation and ability to communicate new offerings across multiple business units. Has led a cross functional team in the delivery of multiple solutions across multiple technologies
  • Ability to operate and present at all levels, and in public forums, to facilitate business discussions, and controls and leads those discussions
  • Ability to relate risks and challenges with other client efforts
10

Senior Data Scientist Resume Examples & Samples

  • Select a function
  • E-business
  • Environment, Health & Safety
  • Information Technology
  • Sales
11

Senior Data Scientist Resume Examples & Samples

  • Expertise in predictive modeling using both supervised and unsupervised learning techniques. Must have knowledge and experience in the following: generalized linear models, ensemble models, resampling methods, model validation and testing, dimensionality reduction, clustering, and Bayesian approaches to data analysis
  • Previous management or teaching experience
  • Excellent capabilities with the basic analysis tools of SQL and Excel
  • Demonstrated academic achievement and an active research agenda in relevant topic areas impact, particularly in “Big Data” environments
  • Strong ability to communicate modeling procedures and results to non-experts
  • Experience with Hadoop is preferred
12

Senior Data Scientist Resume Examples & Samples

  • Programming skills and capability will be pivotal to this role to create working solutions and tools that deliver results. Preferably Python
  • Experience of building Algorithms, Data Mining
  • R, SQL, SAS, and Hadoop would be very useful, but not essential
  • Math/Statistics: Statistical modelling, Supervised Learning
  • Experience of Logistic regression and Classification algorithms
13

Senior Data Scientist Resume Examples & Samples

  • Build statistical models (both predictive and descriptive) for Campaign targeting prioritization, Nurture stream design and optimization, Response management prioritization, Analytics lead scoring, Account modeling, customer value migration, cross sell, churn or any other models meeting a specific business need
  • Develop the organization’s understanding of the business impact and usage of advanced modeling techniques
  • Serving as methodology “guru” across Marketing to identify and implement statistical models, techniques, tools and methodologies that improve our efficiency and effectiveness
  • Conduct data sourcing and integration and build predictive models to analyze customer purchase value, propensity and behavior
  • Analyze install base to identify migration, up sell and cross sell opportunities
  • Business acumen
  • Problem Solver
  • Creative thinker
14

Senior Data Scientist Resume Examples & Samples

  • 8+ years of experience or 6+ years with graduate or PhD of exceptional data mining, statistical analysis and coding to work
  • The ability to balance the “art and science” by solving analytical problems using quantitative and qualitative approaches that will be critical
  • Skills with analyzing and deconstructing big data sets, including knowledge of Matlab, SAS, R, relational databases, and distributed system technologies (e.g., NoSQL)
  • Ability to work independently as well as lead small cross-functional teams
15

Senior Data Scientist Resume Examples & Samples

  • B.S, M.S., or PhD. in Computer Science, Computer Engineering, Applied Mathematics or related field
  • 3+ years of experience in Machine Learning, Statistical Models, and Natural Language Processing, Text Analytics on large data sets
  • Solid understanding of machine learning techniques including: Support Vector Machines, Logistic Regression, Decision Trees, Max entropy, Conditional Random Fields and Unsupervised Learning Methods
  • 1+ year experience with Python
  • 1+ year experience with R
  • Team player with excellent communication skills
  • Publications/Presentations in relevant communities (ICML, NIPS, CVPR, SIGIR, ACM Multimedia) is a strong plus
  • Knowledge of SkLearn, NLTK, WEKA, Mallet, CLUTO, GENSIM and similar toolkits is a plus
  • Legal or financial domain experience is a plus
16

Senior Data Scientist Resume Examples & Samples

  • Providing technical subject matter expertise around advanced and large-scale data analysis
  • Lead customer project activities in one or more different areas as: Customer Insights, Pricing strategy & implementation, Operation/supply chaing analytics, Finance, Risk & Fraud Analytics, Preditctive Maintenance
  • At least 5 years experience in /advance analytics projects helping customer enhance business performance using data insights
  • At least 5 years experience in /strong quantitative and analytical expertise that covers statistics, machine learning / data mining, experimentation methodology
  • At least 5 years experience in leading advanced analytics tools (such as R, SPSS, SAS ...)
  • At least 5 years experience in conducting analyses on unstructured as well as structured / semi-structured data
  • At least 5 years experience in /building predictive model for different business situation
  • At least 5 years experience in Analytics customer Projects
  • At least 5 years experience in Industry consulting
  • Italian: Fluent
17

Senior Data Scientist Resume Examples & Samples

  • Experience solving problems that required the use of machine learning algorithms or statistical modeling
  • Programming skills that allow you to be self sufficient in handling data and prototyping various analysis approaches: Knowledge of SQL, Knowledge of a scripting language such as Python or Perl, Working knowledge of a language for modeling or statistical analysis such as R or Matlab
  • Excellent communication skills and ability to describe complex technical concepts in clear language
18

Senior Data Scientist Resume Examples & Samples

  • Support Development of Advanced Analytics practice: In cooperation with Sr. Director of Retail & Customer Analytics, develop best in class advanced analytics practice for VF and drive analytic culture both corporately and within the brands
  • Brand Consulting: Perform ongoing analytic projects in support of brand strategies and tactics. Topics will include, but not limited to direct marketing optimization, incorporation of unstructured information, sales attribution, ROI analysis
  • Support BI Reporting: In collaboration with brand and D2C leadership, support the development of BI dashboarding to highlight KPI across brands, locations and channels. Work will include multi-source data integration and development in BI tool (Cognos, Tableau)
  • Support Process Improvement: Bring industry best practices to analytic processes to create time efficiencies, so team can broaden efforts to other focus areas
  • Team development: Through peer-to-peer training and direct reports, develop internal talent to expand advanced analytics capabilities – including modeling, automation, and data visualization/presentation techniques
  • Data Infrastructure: In collaboration with infrastructure in IT teams, make recommendations for data architecture strategy
  • Tool Assessment: Develop and deploy analytical tools and data science techniques to analyze complex data sets. Monitor trends in data science and alternative sources to ensure that VF Corporation is in tune with best in class tools and techniques
  • 10+ years of experience in market research/insights/analytics, competitive intelligence or other similar function with demonstrated ability to manage function in a complex environment with multiple constituencies
  • Deep expertise in complex modeling and analytical methodology including, but not exclusively, longitudinal analyses, multi-level modeling and multivariate analyses of variance
  • Demonstrates a sense of calmness under periods of uncertainty or change while dealing with stress in a manner that sets the necessary tone for the team and function
  • High character and integrity, is consistent and acts in line with a clear and visible set of values and beliefs
19

Senior Data Scientist Resume Examples & Samples

  • Graduate degree in statistics / mathematics or related field
  • 5+ year experience data modeling in a multi-terabyte data warehouses and/or other big data platforms. Experience in the financial services industry (banking, consumer finance) is a plus
  • 5+ years coding experience in tools such as Python, R, Java, etc. for statistical analysis and machine learning
  • Prior experience with analytical processing on real-time information via API or other bus technologies
  • Demonstrated experience creating as solution from conceptualization through implementation
  • Must have experience delivering advanced visualizations against enterprise level data repositories
  • Previous experience conducting requirements gathering and design sessions with customers
  • Previous experience producing written deliverables for senior management
  • Excellent oral and written communication skills are a must
  • Experience with big data technologies including, but not limited to, Hive, SQL Spark, Splunk is a definite plus
  • Experience with SAS a plus
20

Senior Data Scientist Resume Examples & Samples

  • Develop highly innovative analytics platform by centralizing data collection that drives data science and analytics capabilities
  • Define creative modeling approaches and strategy
  • Conduct deep data mining and predictive analysis using a variety of technologies
  • Solve highly complex and sophisticated data problems
  • Develop and implement cutting edge algorithms and use advanced quantitative analysis on multiple data sources
  • Lead continuous improvement efforts to ensure the operational needs of the business are being met
  • Research Big Data ideas and implement best practices
  • Devise scalable, maintainable, and reliable services that process large quantities of structured and unstructured data
  • Develop recommendation algorithms to drive customized experience indigital channels
  • Focus on key deliverables that fit into a unified and reliable Big Data infrastructure
  • 10-15% domestic or international travel to corporate or vendor sites, fully reimbursed
  • Telecommuting optional
21

Senior Data Scientist Resume Examples & Samples

  • Provide strategic direction for development of advanced decisioning and analytics to support business needs
  • Research, design, develop, implement and support decision science models for personalization of message content and next-best-action recommendations at Guest engagement points
  • Perform exploratory data analytics to identify patterns in Guest behaviors and preferences
  • Lead collaboration across the WDPR partners to coordinate decision engines development, and optimize the usage of the existing decision engines
  • Serve as decisioning SME offering analytical consultation, market best practices and solutions to achieve business goals and objectives
  • Provide oversight of the decision engine implementation into the NICE Causata decisioning tool
  • Provide day-to-day leadership for the team
  • 7+ years with proven experience in decision science, math, multivariate modeling, statistics, predictive analytics, big data analytics, exploratory data analysis to drive significant business impact
  • Strong knowledge of decision engines and machine learning algorithm creation and optimization
  • Experience working with high-volumes of structured and unstructured data, from varying sources, to detect patterns
  • Experience with web analytics tools such as Omniture, Google Analytics, Webtrendes, etc
  • Familiarity with relational databases and SQL-like query languages
  • Expert knowledge of a scientific computing language such as R or Python
  • Capable of delivering creative solutions and socializing complicated concepts to both technical and non-technical partners
  • Good business acumen with strong ability to solve business problems through data driven quantitative methodologies and provide concise thoughts into proposals, recommendations and findings
  • 5+ years of leading a team responsible for data analysis
  • Travel/Hospitality industry experience
  • Experience with Causata, or NICE Customer Engagement Analytics tool
  • Knowledge of marketing, specifically these disciplines: direct (email, direct mail), digital, social
  • Master’s degree in Statistics, Industrial Engineering, Mathematics, Decision Science, Econometrics, or related fields
22

Senior Data Scientist Resume Examples & Samples

  • Develop and deliver core data mining and machine learning algorithms and solutions supporting AOL’s product roadmap and future needs
  • Extend and enhance the existing processes, methods, and infrastructure to improve the efficiency and effectiveness of the organization
  • Innovate, develop, evaluate, and deliver cutting edge solutions to novel problems in the areas of demographic targeting, data collection / cleansing, and pattern matching
  • Proactively suggest data analysis and technical solutions which can inform and help direct the business
  • Will need to hypothesize, analyze root causes and then generate data-driven solutions
  • Contribute to the design and implementation of clean and robust software within a complex business landscape
  • Interested in the development of Intellectual Property assets
  • Master’s degree in mathematics, statistics, software engineering, or computer science
  • Deep technical understanding of data mining, machine learning, statistical NLP, statistics, data science
  • Expert in several quantitative software tools (ex. R, Python, SQL, Mathematica, etc.)
  • Experience working with high dimensional data sets
  • Pragmatic, team-oriented, builds rapport and respect
  • Strong communication, writing, and critical thinking skills; attention to detail
  • Track record or desire to mentor top technical talent in the areas of data mining, analytics and machine learning
  • 3+ years experience with C#, Java, or C++
  • 3+ years experience with databases and schema design
  • Strong computer science fundamentals in data structures, algorithms, and complexity analysis
23

Senior Data Scientist Resume Examples & Samples

  • M.S. or Ph.D. degree required in a quantitative discipline
  • 1+ years of academic and/or industry work building machine learning or statistical models on data sizes greater than 100 million rows
  • Familiar with Unix command-line tools for processing data
  • Familiar with data cleansing and ETL processing
  • Passionate about combining academic research and empirical research to solve challenging data problems
  • Proven ability to take ideas from research to production is a strong plus
  • Self-starter and entrepreneurial ability. Data Science requires a lot of false starts and constant testing before things begin to work. Must be willing to tolerate failures
  • Programming skills in Java, Scala or Python
  • Experience with data from Ad Tech, Online Media or E-Commerce a strong plus
  • Experience with Map/Reduce or other Big Data processing frameworks, such as Apache Spark, a strong plus
  • Self-driven but able to collaborate in teams
24

Senior Data Scientist Resume Examples & Samples

  • Research, define, and develop new methods for analyzing and measuring quality of product features and product releases
  • Design methodologies to model components of distributed systems
  • MS/ PhD in fields like computer science, mathematics, statistics, machine learning, operations research, data mining, AI
  • Understanding of public cloud design patterns and considerations in the areas of distributed systems, distributed storage systems, big – data, data mining, information retrieval
25

Senior Data Scientist Resume Examples & Samples

  • Establish data science as a discipline within Consumer & Market Knowledge and Ubisoft as a whole
  • Deliver modelling algorithms for the department, where your skills help us in delivering recommendations to our followers on digital channels
  • Add to our global insights agenda by developing data visualization, data mining and advanced analytics to extend our current insights generation
  • Deliver ad-hoc analytics to internal stakeholders in the wider organization and service other analytics initiatives within production and marketing
  • Experience with statistical modelling, data extraction and modelling
  • Hold a degree in Math/Statistics with a strong experience in programming. Alternatively you have substantial practical experience or a degree in Engineering with a significant focus on statistics and modelling
  • Have 5 years of experience with statistical modelling, data extraction, manipulation, and visualization
  • Have 2 years of experience in project management
  • Proficiency in at least one programming language, preferably R
  • Have a proven track record of understanding business analyses and supporting them, just as you know how to translate analytics into insights for stakeholders
  • Need to be able to travel to internal projects for a limited amount of time
  • Speak and write English fluently
26

Senior Data Scientist Resume Examples & Samples

  • Intellectual Curiosity - continually being curious and wanting to learn new things and not being afraid of trying new things
  • Impact and passion to move the bottom line - we are looking for people that are really passionate about understanding the higher-level business goals and work towards moving them
  • Failing Fast – over 90% of our ideas fail. We need to understand how to build the right heuristics and tests to fail as fast as possible
  • Background in Computer Science, or equivalent technical field
  • Software development skills in one or more high level languages (C#/C/C++/Java/F#)
  • Experience working with large data sets and working with distributed computing tools (e.g. Cosmos, Hadoop, Spark, Hive, MapReduce, etc)
  • Knowledge of machine learning and data mining techniques in one or more areas of statistical modeling methods, time series, text mining, optimization, information retrieval
27

Senior Data Scientist Resume Examples & Samples

  • 5+ years demonstrated experience using data mining and machine learning skills to solve real-world problems
  • Skill in identifying patterns and trends in a large ecosystem of disparate data sources and building the necessary processes and/or automation to highlight trends (both positive and negative) and opportunities
  • The ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
  • The ability to own data research initiatives, working in a self-directed fashion with a broad spectrum of collaboration from different teams
  • Customer focus and curiosity
  • Excellent communication, presentation, and cross team collaboration skills
  • Bachelor or Master’s degree in quantitative field such as mathematics, statistics, operations research, or engineering/technology with an emphasis on statistical analysis; or applicable experience
28

Senior Data Scientist Resume Examples & Samples

  • Become a subject matter expert and trusted advisor in the analytics discipline
  • Demonstrate excellent organization skills throughout the development of analytical solutions (data analysis documentation, hypothesis documentation, code management, etc.)
  • Build and deploy prototype solutions to demonstrate ideas and prove concepts
  • Effectively communicate with project team members and sponsors throughout the project lifecycle (status updates, gaps/risks, roadblocks, testing outcomes, etc.)
  • Work independently and collaboratively (as needed) within the team to achieve the desired outcomes of an analytical project
  • 8 - 10 years experience developing predictive models, forecasting models and/or machine learning algorithms in a large-scale, corporate environment
  • 5+ years experience developing analytical models/solutions in a financial services environment
  • Proven ability to strategically manage complex, highly-visible analytical projects from concept through implementation
  • Proven experience continuously improving analytical models/algorithms to achieve better outcomes
  • Proven experience leveraging job automation applications and environments (i.e. CRON, Control-M, etc.)
  • Expert-level abilities in at least one of the following: SAS, SQL, R, Python
  • Demonstrated ability to effectively manage all facets of the analytical project lifecycle (data discovery/exploration, hypothesis testing, code development, testing/validation, model deployment, etc.)
  • Strong affinity towards analyzing data and writing code
  • Hands-on experience with a wide variety of predictive modeling, machine learning, data mining, statistical/text mining, and optimization algorithms
  • Proven ability to perform quality control checks during the model/analytical solution development lifecycle
  • In-depth knowledge of and demonstrated adherence to commonly used coding standards (header, change control log, code segmentation, code commentary, etc.)
  • Outstanding critical thinking and problem solving skills
  • Self-starter mentality with the ability to delegate/collaborate with others
  • Ability to translate ambiguous business problems into a conceptual mathematical architecture
  • Passion for continuous learning and professional development
  • Deep curiosity, creativity and imagination
29

Senior Data Scientist Resume Examples & Samples

  • Hadoop big data framework
  • Building predictive regression and classification models
  • Building time series and forecasting models
  • Object-oriented languages, including JAVA, Python, and C/C++
  • Version control systems, including GIT
  • Predictive modeling technique, including Support Vector Machines
30

Senior Data Scientist Resume Examples & Samples

  • Answer complex business questions by using appropriate statistical techniques on available data or designing and running experiments to gather data
  • Rapidly develop novel applications of classification, forecasting, simulation, optimization, and summarization techniques
  • Work closely with cross functional teams to encourage statistical best practices with respect to experimental design and data analysis
  • Create compelling interactive visualizations and presentations to enhance decision making capabilities throughout the company
  • M.S. or Ph.D. in relevant technical field such as Statistics, Computer Science, Engineering, or Economics
  • Expert knowledge of an analytical tool such as SAS, R, Matlab, STATA, or Python
  • Experience with relational databases and SQL
  • Ability to communicate complex quantitative analyses in a clear, precise, and actionable manner
  • Familiarity with visualization tools such as Tableau or Spotfire
31

Senior Data Scientist Resume Examples & Samples

  • Executes standard exploratory and ad hoc data analysis. Interprets and presents results using tools such as PowerPoint, Excel or Tableau
  • Applies cleansing, discretization, imputation, selection, generalization etc. to create high quality features for the modeling process
  • Uses big data, relational and non-relational data sources to access data at the appropriate level of granularity for the needs of specific analytical projects. Maintains up to date knowledge of the relevant data set structures, access levels and ownership information
  • Participates in the analysis and formalization of the business problems
  • Consistent exercise of independent judgment and discretion in matters of significance
32

Senior Data Scientist Resume Examples & Samples

  • Analyze data to identify outliers, missing, incomplete, and/or invalid data
  • Ensure accuracy of all data from source to final deliverable by creating automated quality checks
  • Assist in the development of analytic tools, KPIs, dashboards, and systems to help build out the analytics platform
  • Create, automate, and maintain reports and visualizations (e.g., behavioral trends across customer segments, global consumption of VOD and live stream, digital media attribution, etc.)
  • Work with data warehousing team to design optimal data architecture for BI tools
  • Work as a client contact for analytics, partnering with various departments to identify priority dashboards and reports to better serve the company
  • Well-rounded individual with the ability to write code to query and transform both unstructured and structured data
  • Should enjoy generating actionable insights by mining and modeling data and be passionate about answering challenging questions and telling stories with data and visualizations
  • Self-motivated, attentive to detail, and driven to continuously improve analytics skill set
  • SQL, AWS Redshift, Python, Big Query, Google Analytics, Excel, and Tableau
  • SAS, SPSS and/or R
33

Senior Data Scientist Resume Examples & Samples

  • Establish scalable, automated processes for large scale data extraction, model development, model validation, and model implementation
  • Mentor PhD data science interns on model design, feature building, model evaluation, and deployment
  • Cover Letter which should include
34

Senior Data Scientist Resume Examples & Samples

  • Devise and implement methods for adaptive learning with controls on effectiveness, methods for explaining model decisions where necessary, model validation, A/B testing of models
  • Create predictive models for consumer behavior using any and all data available in our clusters
  • Experiment with in-house and third party data sets to test hypotheses on relevance and value of data to business problems
  • Work with business stakeholders to aid with data driven business decisions
  • Work with engineering to implement predictive models in production environment
  • Work with data and analytics team to drive availability of relevant data, tools, and infrastructure
  • MS/PhD in Computer Science, Operations Research, Statistics or highly quantitative field (or equivalent experience) with strength in Machine Learning, Data Mining, Statistical or other mathematical analysis
  • Hands-on experience with predictive problems using techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks
  • Expert in creating accurate models using machine-learning libraries in Python/R/Matlab or a language of your choosing
  • Experience working with Hadoop, MapReduce, Pig, Hive, Spark and/or Mlib
  • Experience working with relational databases like MySQL
35

Senior Data Scientist Resume Examples & Samples

  • Develop, expand and evaluate demographic models, including cluster modeling and distance metrics
  • Develop, expand and evaluate recommendation engines for securities and financial products
  • Partner with JPM quants and technologists to model, price, and implement trading and/or risk management strategies across all asset class
  • Participate in discussion of data modeling and algorithmic design
  • Participate in discussion of product design and usage, including engagement with end users
36

Senior Data Scientist Resume Examples & Samples

  • Collaborate with Advanced Analytics and Data Engineering leads to establish analytic standards and platforms that scale and can be leveraged in various initiatives throughout the organization
  • Communicate complex concepts and the results of analyses in a clear and effective manner business stakeholders
  • Communicate with leaders to maximize the effectiveness of the data science initiatives
  • Demonstrated experience in applying Machine Learning to at least one of the areas: Cluster Analysis, Probabilistic Modeling, Structured Prediction, Neural Net, or Anomaly Detection
  • Data Wrangler: You know how to move data around, from a database or an API, through a transformation or two, a model and into human-readable form (ROC curve, Excel chart, map, d3 visualization, Tableau, etc.). You probably know Python, Java, R, Storm, Julia, SQL, Matlab, Mahout, or think everything can be done in a Perl one-liner
  • Advanced knowledge of two or more of the following analytics languages/toolkits: Python (specifically with scipy, numpy, scikit-learn etc), R, SQL, SAS, SPSS, or Matlab
  • Experience operating in a Linux environment
  • Recent experience building Recommender Systems is a big plus
  • You're a self-starter that's highly accountable and will take ownership of delivering your work
  • 2+ years of professional experience as a Data Scientist
37

Senior Data Scientist Resume Examples & Samples

  • Learn how to build and sustain engagement from all levels of an organization
  • Programming skills (esp. related to data technologies like Python, PERL, Java, C#, etc.)
  • Stats or data analysis experience working with advanced tools like R, SAS, SPSS, advanced Excel, etc
  • 3 or more years experience using data to impact critical product or business decisions
  • A proven track record of collaborating across organizational boundaries and delivering great results
  • Excellent analytical, communication, technical leadership, and interpersonal skills
  • Solid writing, presentation, and data visualization skills
  • Familiarity with software development, database design, and online service development
38

Senior Data Scientist Resume Examples & Samples

  • You will be in charge of the follow-up and evaluation of existing algos and propose improvements and new approaches
  • You will participate to the scientific communication efforts of AlephD
  • You have a MS degree or PhD from a top-notch institution in a field such as Computer Science, Mathematics, Physics, Statistics, quantitative Economics or Finance; or you have a track record proving similar skills
  • You have commercial professional experience in data-science ideally using Hadoop or Spark
  • You have a strong taste for statistical modelling and data analysis
  • You have good expression skills and can expose complex technical problems with ease
  • You are eligible to work in France
39

Senior Data Scientist Resume Examples & Samples

  • Handling large amounts of data using various tools, including your own. All programming languages welcome, especially R, Python, SQL, and C#
  • Superior verbal, visual and written communication skills
  • Data hacking skills and knowledge in various analytical programming languages: R, SQL, Python
40

Senior Data Scientist Resume Examples & Samples

  • Work on challenging fundamental data science problems in online advertising
  • Propose and develop solutions independently and leading a group of other data scientists
  • Prepare white papers, scientific publications and conference presentations
  • Develop best practices for instrumentation and experimentation and communicate those to product engineering teams
41

Senior Data Scientist Resume Examples & Samples

  • Dive deep into data to find key insights that impact early stage product development
  • Analyze multiple large data sets using data mining, statistics, and database techniques
  • Work with multiple Windows Application groups to formulate their business decisions as data science problems
  • 5+ years demonstrated history of innovative thinking and problem solving skills in Big Data problems
  • Ability to deliver on ambiguous projects with incomplete data
  • Strong hands-on experience in decision sciences, machine learning & data mining
  • Deep familiarity with statistical models & methods (time-series analysis, regression analysis, experimental design, hypothesis testing, etc.)
  • Experience on large scale computing systems like COSMOS, Hadoop, Mapreduce and/or similar systems is a big plus
  • Strong skills in SQL, R, Python, SAS and related tools for large scale analysis
  • Master’s Degree in Statistics, Mathematics, Econometrics, Machine Learning or a related field required. Doctorate/PhD preferred
42

Senior Data Scientist Resume Examples & Samples

  • Participate in the development of new analytic products to optimize fit, flatter, and fashion of apparel and footwear
  • Develop insights and metrics for retail partners that support their site marketing and personalization efforts. Specify analytics tools for retailers to use
  • Develop insights and metrics for brand partners to support their product design and marketing efforts; specify analytics products for brand partners
  • Ph.D. in a quantitative field with research work including a significant statistics or quantitative analysis component. Applicable fields include, for instance, applied mathematics, statistics, experimental physics, astronomy, chemistry, engineering, etc
  • Experience developing and applying statistical models to extract value from real-world data. Experience with advanced statistical tools (e.g. R, pandas, etc.)
  • Experience using machine learning methods to develop solutions to real-world problems
  • Some software engineering experience desirable
  • Strong listening and communications skills
  • Thrives in a dynamic and collaborative environment
43

Senior Data Scientist Resume Examples & Samples

  • Strong interpersonal, oral and written communication and presentation skills, ability to communicate complex findings in a simple manner
  • Enjoy discovering and solving problems; proactively seeking clarification of requirements and direction; being a self-starter who takes responsibility when required
  • Understanding of public cloud design patterns and considerations in the areas of distributed systems, distributed storage systems, big - data, data mining, information retrieval
44

Senior Data Scientist Resume Examples & Samples

  • It can tell a client in real time ‘What happened’, ‘Why did it happen’ and ‘Will it happen again’?
  • Keeps everyone on the same page by looking at the same Business Transaction data and metrics
  • Keeps the focus on metrics that translate to the business value the application delivers; dive in deeper when appropriate
  • Identify resolution criteria, assign ownership
  • Take lessons learned to improve development, test, deployment, and production processes
  • Expertise in Data Mining, Data wrangling, and data munging using one or more of the most commonly used data science tools: R, Python, SAS, SPSS
  • Experience in end-to-end data science and engineering activities
  • Expertise in client engagement, data science consulting type activities
  • Must have led a team of data engineers and data scientists in leading data science engagements
  • Experience with analytics in IT and IoT space is a plus
  • Knowledge and experience in Hadoop (map reduce paradigm) etc
  • Must be hands-on and must have worked on implementing machine learning and data mining algorithms
  • Passion for finding meaning in large data sets and identifying actionable results from this meaning
  • Excellent communication skills (both written and verbal) and interpersonal skills
  • Experience working with and transforming large data sets
  • Understanding of business value and how this relates to actionable results
  • Ability to identify or interpret many inputs and requirements then transforming them into actionable plans
  • Ability to take vaguely defined data sets and requirements then proactively identify and partner with needed SMEs to provide interpretations tailored to individual client needs
  • Ability to visualize data results into meaningful workflows including charts and graphs
  • Experience working with IT management software is a plus
  • Experience in scripting languages with experience in scripting to integrate software solutions is a plus
  • Additional Skills (optional) Scala, Spark, Storm, IBM BigInsights, SAS, SPSS, GraphLab, H20, Mahout, Hive
  • Product Knowledge: At least 3 of the following: R, Python (Scikit-learn, numpy, etc), SAS, SPSS, MATLAB/Octave, Hadoop (Map Reduce programming),
45

Senior Data Scientist Resume Examples & Samples

  • Analyse large, complex datasets to reveal underlying patterns, correlations and trends
  • Drive development of machine learning techniques to model product demand based on customer behavioural and preference segments
  • Create prototypes for predicting appropriate full and sale price for new products and turn machine-learning outputs into operational data products
  • Time series analysis on product sales and conversion
  • Design, set-up and conduct large-scale experiments to test hypotheses and drive product development
  • Research and leverage new machine learning methodologies to improve current products and influence the future roadmap
  • Leverage quantitative techniques to answer non-routine business problems
  • Mentor other Data Scientists, Analysts and Data Engineers to implement statistical analyses and data pipelines
  • Educate other Analysts and business team members to expand impact to additional products or business units
  • Act as lead on cross team projects involving multiple stakeholders
  • A PhD in a quantitative subject
  • Experience in solving large analytical problems using statistical, machine learning or other quantitative methods (e.g. supervised/unsupervised learning, graphical models, time series analysis, statistical testing)
  • Experience with distributed computing (Hadoop/Spark)
  • A hackers mentality and comfort using open source technologies and Unix scripting
  • Interest in keeping up with state-of-the-art machine learning by attending and submitting papers to relevant conferences
46

Senior Data Scientist Resume Examples & Samples

  • 3+ years of experience working with large data sets or doing large scale quantitative analysis
  • Fundamental understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo
  • Strong coding abilities. Preference towards knowledge of one of the following open source languages: Scala, Java, C++ or C#. We use Python and C#
47

Senior Data Scientist Resume Examples & Samples

  • Wrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own. All programming languages welcome, especially R, Python, SQL, Java, JavaScript, and C#
  • Finding insights and forming hypothesis in the data with various machine learning, statistical, and data mining techniques: e.g. regression, classification, optimization, p-values analysis, time series modeling, anomaly and outlier detection
  • Building and owning data models to monitor live site metrics : what information should we be capturing to analyze the root cause of an outage when it’s happening? What information needs to be captured to predict and prevent a similar outage in the future?
  • Designing experiments and new measurements, understanding the resulting data, and producing actionable, trustworthy conclusions from them
  • A graduate degree in computer science or a quantitative domain plus hands-on software engineering and data science experience
  • 3+ year experience delivering, scaling, and owning highly successful and innovative data science products with your fingerprints all over them
48

Senior Data Scientist Resume Examples & Samples

  • Proven experience implementing and deploying advanced analytics (Machine Learning) solutions for large enterprise or commercial customers in complex heterogeneous environments
  • Expertise in Microsoft AzureML and/or Microsoft R Server
  • Expertise in open source and/or competitive platforms
  • Working knowledge of specialized tools and solution providers whether they be Microsoft partners or competitors
  • Knowledge of full application life cycle design tools and methodologies
  • Data Science degree with enterprise experience in Machine Learning / Statistics
  • At least on of the ML related technologies ( SAS, SPSS, RevR, Azure ML )
  • Data prep with industry standard ETL tools, R, Python, etc. and with Visualization tools ( Tablue, QlikView, PowerBI, etc )
  • Big Data stack: MapReduce, Hadoop, Sqoop, Pig, Hive, Hbase, Flume
  • ETL technologies: Talend, Pentaho, Informatica, etc
  • DW: Relational (Oracle, Teradata, Netteza, SAP HANA ), columnar (RedShift, Vertica), noSQL (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores)
  • Analytical tools, languages, or libraries: SAS, SPSS, R, Mahout)
49

Senior Data Scientist Resume Examples & Samples

  • Prototype and build new models in recommender systems and NLP
  • Creatively explore how to use data to understand user behavior to improve personalization models
  • Partner with engineering teams to build and deploy your models into production
  • Design experiments to validate hypotheses to answer business questions
  • Prepare visualizations and create a cohesive narrative to present and explain your findings to the rest of the organization
  • BS in Computer Science, Applied Mathematics, Operations Research, Engineering or related discipline preferred, or equivalent experience
  • Advanced skills in a scripting language such as Python
  • Expertise in at least one high level statistical software package (R or Matlab)
  • Experience working with large amounts of data
  • Experience working with SQL
  • Able to communicate findings clearly to both technical and non-technical audiences
  • MS/PhD in a quantitative discipline: Statistics, Applied Mathematics, Operations Research, Computer Science, Engineering, Economics, etc. preferred or equivalent experience
  • Experience working on NLP, Text Mining, or Recommender Systems
  • Experience working with large amounts of real data
  • Advanced skills in Scala
  • Experience in MapReduce paradigms such as Spark
50

Senior Data Scientist Resume Examples & Samples

  • Acquire and/or synthesize datasets to support development of analytic solution features
  • Develop prototypes of key data manipulations or mathematical modeling elements that are to be embodied in analytic solutions, using software tools appropriate for the modeling problem
  • Training in accounting
  • Recognized expertise in an analytics discipline as evidenced by publications or awards
51

Senior Data Scientist Resume Examples & Samples

  • Converting a business problem into an analytical solution in collaboration with our client and IBM colleagues
  • Leading other Data scientists and consultants in projects, hands-on and tactically
  • Identifying approaches to improve accuracy and effectiveness of analytics models
  • Master's Degree or PhD in a quantitative field like Mathematics, Statistics, Operations Research and similar
  • Hands-on analytic skills, yet also a strategic thinker who can see the 'big picture' while handling the details
  • Experience in hands-on use of statistical packages (i.e. SPSS, SAS, R, Python)
  • Experience in identifying and defining requirements and turning functional requirements into a predictive or prescriptive analytics solution that address difficult business solutions
  • Experience in optimizing software package (i.e. CPLEX)
  • Experience in solving clients' analytics problems and effectively communicating results and methodologies
52

Senior Data Scientist Resume Examples & Samples

  • Deep machine learning background
  • Experience with leading services ML delivery work streams
  • Master degree or above in ML or Statistics or a related quantitative field
53

Senior Data Scientist Resume Examples & Samples

  • 5+ years of experience in auto industry business and bank/finance business
  • 5+ years of programming experience in R, MATLAB, NAG, C# and/or SAS required
  • Ph.D. in a quantitative field such as Statistics, Economics, Mathematics, Physics, Operation Research or Quantitative Finance
  • Experience with visualization software tools such as qlikview, tableau
  • Experience with Microsoft EXCEL, PowerPoint and Word. Ability to create and manipulate pivot tables and graphs. Some experience with SQL and EXCEL macros
  • Demonstrated proficiency with simulation techniques such as Monte Carlo
  • Strong knowledge of optimization techniques (e.g. linear/nonlinear/dynamic programming)
  • Extensive experience on parallel/grid computing, and programming in a variety of software platforms
54

Senior Data Scientist Resume Examples & Samples

  • Collaborate closely with other CMR Advanced Analytics team members to add elements of storytelling and impact across the portfolio of work
  • Own and manage the project calendar for the team as well as consistently publish team priorities to core stakeholders
  • Create client-facing communications (PowerPoint, email, etc.) from advanced analytics outputs that enable internal marketing stakeholders to make fact-based, strategic business decisions (clearly frame the current business situation, represent the current and future state of the market, and draw logical, fact-based conclusions regarding business implications and the recommended course of action)
  • Demonstrated success collaborating and working across a broad set of team members is required
  • Skill and passion for creating business communications that influence business decision makers to think differently and take action is a must. Experience in developing and presenting communications from complex analytics in language easily consumable by non-experts
  • Focus on the big picture: while everybody focuses on their specific area, this person needs to keep an eye on the bigger picture and how the different aspects come together
  • Ability to maintain balance between solid “pragmatism” and “scientific rigor” to meet the needs of a dynamic business
  • High energy, maturity, and leadership with the ability to serve as a unifying force and to position communications discussions at both the strategic and tactical levels
  • Advanced Analytic and market research exposure: understanding of statistical methods such as bayesian networks, regression/ marketing mix modeling, machine learning (factor, cluster, other classification and regression algorithms applied to business problems, neural networks etc). Knowledgeable of quantitative and qualitative research techniques and their applications to business questions (e.g. TURF, simulating the appeal of product-feature combinations, recommending future scenarios to improve brand, product impact)
  • Marketing Knowledge: Familiar with the Marketing discipline in terms of the strategy, plans and decisions that marketers make
55

Senior Data Scientist Resume Examples & Samples

  • A minimum of 5 years industry experience solving analytical problems using quantitative approaches
  • Bachelors or Master’s degree in quantitative field such as mathematics, statistics, operations research, or engineering/technology with an emphasis on statistical analysis; or applicable experience
  • Experience in applied machine learning
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
  • Expert in querying and analyzing data using Hive, SQL, Python, R, and/or C# including the skills necessary to develop metrics, create reports, and interpret analytical results
56

Senior Data Scientist Resume Examples & Samples

  • Personalization and audience modeling
  • Content classification and understanding
  • Semantic understanding and classification of images
  • Optimization of content for different delivery channels (web, mobile, social, etc.)
  • 2+ years developing machine learning models in industry
  • Proven ability to develop machine learning models that solve business problems
  • Strong understanding of modern machine learning techniques including regression, classification, clustering, and their use with text data
  • Expert in at least one of the following: NLP / Computational Linguistics, Recommender Systems, Deep Learning
  • Strong programming skills (Python / Java / Scala preferred)
  • Advanced degree in a quantitative field
57

Senior Data Scientist Resume Examples & Samples

  • 5+ years of industry experience with a proven track record of using advanced data analysis to drive significant business impact, or demonstrated academic achievement and an active research agenda in relevant topic areas
  • Proficiency with at least one language for data analysis, such as Python or R
  • Excellent capabilities with SQL
  • Interest and proficiency in answering complex business questions using statistics, machine learning, and linear algebra
  • Experience with Spark, Hadoop, or another "big data" technology is preferred
  • Education: Master's Degree in statistics, math, engineering, computer science, or another quantitative discipline or 7 years of equivalent experience required. Doctorate/PhD preferred
58

Senior Data Scientist Resume Examples & Samples

  • 5+ years of experience as a Senior Data Scientist
  • Experience in a quantitative field
  • Machine learning expertise with ability to apply algorithms at Big Data scales
  • Experience analyzing time series data
  • Demonstrated ability to multitask
  • Strong coding skills with Python or R as well as SQL and AWS
59

Senior Data Scientist Resume Examples & Samples

  • Passion for business and drive to achieve
  • Demonstrate Analytical thinking capability
  • Hands on exposure to tools like R, Python, SPSS
  • Excellent communication and ability to connect with CXO
  • Ability to write use cases and approach problems with a holistic vision
60

Senior Data Scientist Resume Examples & Samples

  • Extensive data analysis/processing experience (5+ years)
  • Data Science experience (3-5 years)
  • Bachelor’s or Master’s degree in Computer Science or Statistics or a related field (PhD preferred)
  • Strong theory/algorithm background and very good understanding on how to apply advanced knowledge to solve real problems
  • Experience with R, Python, Azure ML, Cosmos, SQL is a plus. Prior experience building forecasting models is desirable
  • Ability to write code is a big plus. Familiarity with SQL is another big plus
61

Senior Data Scientist Resume Examples & Samples

  • Engage broadly with the business to frame, structure and prioritize business problems where analytic projects or tools can have the biggest impact on Nordstrom’s business
  • Perform large-scale statistical research, analysis, and modeling in the areas of web analytics, supply chain optimization, and forecasting
  • Research new analytical methods and tools for optimizing the customer experience
  • Masters degree in Computer Science, Mathematics, Statistics or equivalent education and experience required
  • Experience working with NoSQL data environments and tools such as Hadoop, Spark, DynamoDB
62

Senior Data Scientist Resume Examples & Samples

  • Extract actionable insights from huge volumes of rich data using data mining, statistics, and database techniques. The goal is to measure/understand user experience, system performance, and business health in order to generate actionable insights that help us offer solutions that increase user satisfaction
  • Develop multi-variant forecasting models for Microsoft products like Office 365, Windows, Xbox, Azure and identify product simplification opportunities
  • Work with product engineering and Customer Support on identifying problems in different areas where data mining/machine learning/statistics can help. Explore and develop solutions to these problems. Act as an expert in the area of data mining/machine learning/statistics
  • Lead and design experimentation framework for the Data Science team
63

Senior Data Scientist Resume Examples & Samples

  • Implements activities that generally impact 1 or 2 components / processes of the work of own unit / team / projects
  • Assigned to initiatives that may involve other business unit(s)
  • May lead and recommend business decisions for 1 or 2 business functions
  • Develops and may lead in the execution of statistical and mathematical solutions to business problems within business unit
  • Frames problem then determines intended approach and quantitative methods to develop solution
  • Uses analytical rigor and statistical methods to analyze large amounts of data, culling actionable insights using advanced statistical techniques such as predictive statistical models, customer profiling, segmentation analysis, survey design and analysis and data mining
  • Designs experiments to answer targeted questions
  • Develops materials to explain project findings to Management
  • Develops new algorithms and mathematical approaches to understand the company's audiences and solves complex business problems such as optimizing product performance, revenue and adoption
  • Researches new ways for modeling and predicting end-user behavior
  • 3+ years of progressively complex Data Science or analytics experience
  • Bachelors degree or equivalent in MIS, Computer Science, Data Science or related field
64

Senior Data Scientist Resume Examples & Samples

  • PhD in any field with advanced training on statistical and experimental methods
  • 10+ years of experience using advanced statistical tools
  • Proficiency in the following methods: predictive modeling, regression and classification, time-series, network analysis, experimental and quasi-experimental methods. Working knowledge of Bayesian estimation and methods
  • Advanced knowledge of R, Linux (bash), Python (Pandas, NumPy, SciPy, Scikit-Learn, NLTK, networkx), SQL (MySQL, PostgreSQL) and Spark (ML/MLlib)
  • 2+ years of full-time experience working as a data scientist in the media industry
  • 2+ years of experience developing data pipelines, automated information retrieval and processing systems, as well as advanced analytics tools for research teams and other stakeholders
  • 2+ years of experience working with AWS
  • 2+ years of experience with audience segmentation, content recommendation, AB testing
  • Deep knowledge of experimental methods (AB testing)
  • Working knowledge of distributed file systems (hdfs), cluster and distributed computing (Spark)
  • Solid knowledge of Spark and its machine learning libraries
  • Working knowledge of natural language processing methods and tools
  • Ability to create and maintain clusters for the purposes of running distributed jobs
  • Prior experience working with survey data
  • Substantial experience designing, prototyping, testing and implementing content recommendation algorithms
  • Working knowledge of diverse API’s (e.g. Facebook, Twitter)
  • Strong influence and relationship management skills; comfortable interacting with all management levels, as well as prior experience in providing strategic analysis and consulting
65

Senior Data Scientist Resume Examples & Samples

  • Evaluate Cognitive capabilities that exist or need to be developed by use of Watson APIs to help optimisation of the Delivery Processes within the Service Areas
  • Run the Management System across all Service Line Engineering Teams, TI&A. GPOs to ensure that there is the right level of cadence to get the outcomes for the service areas
  • Develop Analytics/Cognitive capabilities that make the Processes competitive
  • Work with the GPO, Solution Owners and Data Science Teams to transform the processes to derive the value / benefits for the service line
  • Work with the GPO and Delivery Teams to run Proof of Concepts using Agile Methodology to ensure there is a minimum Viable Product and agile improvements thereafter
  • Work with the GPO and Solution Owners to help transform the way these processes work - driving the right change management and transformation methodology
  • Define and Measure the Value and Metrics to articulate the Value
  • Harvest User Stories/ Case Studies needed to incentivate the Users
  • Define experiments, hypothesis, metrics, value
  • Understand how Managed Services Delivery Processes work, Delivery Model
  • Challenge the way things work and look at how Analytics / Cognitive capabilities and Automation can work together
66

Senior Data Scientist Resume Examples & Samples

  • Exploring and understanding data, building advanced analytical models, and presenting the resulting models to any level of audience
  • Designing and driving the creation of new standards and best practices in the use of statistical modeling and optimization
  • Directing special studies and analyses for unique business problems and scenarios
  • Identifying algorithms or products with high intellectual property content, evaluating their potential for patents, oversee patent applications when appropriate, and ensuring intellectual property protection for Cox Automotive
  • Develop, research, and explore in the areas of statistics, machine learning, experimental design, optimization, simulation, and operations research
  • Interpret and develop solutions to business problems using data analysis, data mining, optimization tools, and machine learning techniques, and statistics
  • Develop advanced statistical models utilizing typical and atypical methodologies
  • Design large-scale models using Logistic Regression, Linear Models Family (Poisson models, Survival models, Hierarchical Models, Naïve-Bayesian estimators), Conjoint Analysis, Spatial Models, and Time-Series Models
  • Design large scale models using linear and mixed integer optimization, non-linear methods, and heuristics
  • Design large scale discrete-event and Monte Carlo simulation models
  • Leverage big data to solve both tactical and strategic business problems
  • Identify, understand and evaluate new analytic and data technologies to determine the effectiveness of the solution and its feasibility of integration with Cox Automotive’ s current platforms
  • Develop and update data models for statistical modeling purposes, tracking results against forecasts, and re-specifying when required
  • Design and deploy data-science and technology based algorithmic solutions to address business needs for Cox Automotive
  • Act as a strategic thought partner and propose solution alternatives in alignment with business objectives
  • Analyze customer and economic trends that impact business performance and recommend ways to improve outcomes
  • Collaborate with teammates and customers to set analytic objectives, approaches, and work schedules
  • Develop innovative approaches to accomplish short- and long-term objectives
  • Develop, coach and mentor team members within the department
  • 7+ years’ experience performing advanced quantitative analyses
  • Ability to apply advanced statistical methodologies such as mixed model (random and fixed effects), simultaneous equations, ARIMA, neural networks, and multinomial discrete choice
  • Ability to apply mathematical operations to such tasks as cluster analytics, sampling theory and design of experiments, analysis of variance, correlation techniques, and factor analysis
  • Ability to apply advanced optimization methodologies such as linear and mixed integer optimization
  • Ability to apply advanced simulation modeling methodologies and techniques
  • Ability to utilize complex computer operations--including intermediate programming in 3rd and 4th generation languages, relational databases, and operating systems--and advanced features of software packages, i.e., word-processing, spreadsheets, graphics packages, etc
  • Intermediate to advanced experience in Statistical Software (e.g. SAS, SPSS) and database applications
  • Ability to manipulate, analyze, and interpret terabytes of data
  • Demonstrated experience in organizing, prioritizing, and coordinating complex team efforts
  • Experience with MS Office (Word, PowerPoint, Excel, Project, Visio)
  • Experience in working with executives or strategic planning departments to set and/or manage to corporate level strategies is a plus
  • The employee hired into this role may sit in Burlington, VT or Atlanta, GA. Reasonable relocation expenses offered with this role
67

Senior Data Scientist Resume Examples & Samples

  • Research and design algorithms for use in personalised discovery services (e.g. recommender systems and search engines)
  • Build and deliver algorithms in production environments, typically as services
  • Evaluate how these algorithms perform in live services and improve them to move relevant business goals
  • Demonstrate, communicate and promote the value of Data Science in discovery products both inside and outside the company
  • What you'll be doing
  • Research, develop and evaluate algorithms to power discovery services (e.g. recommender systems, search engines)
  • Identify, obtain and prepare large scale data sets for training and testing algorithms (e.g. data cleaning, data normalisation, data linkage)
  • Evaluate algorithms through controlled offline and online experiments (e.g. A/B testing)
  • Build proof of concept prototypes demonstrating these algorithms in action
  • Productionise prototypes with the support of skilled engineers to make reliable, scalable systems
  • Working with UX, Product and Business teams to deliver end-to-end discovery products
  • Deliver presentations that communicate the value of discovery technologies to the business
68

Senior Data Scientist Resume Examples & Samples

  • Design, develop and manage large scale, big data-driven predictive models that are integrated with key product features. Some examples that are already under development or deployed include
  • You’re a critical thinker with an ability to apply your analytical insights and modeling skills to a specific domain and application
  • Ability to write analytics code that can run in our production environment
  • Advanced knowledge of two or more of the following analytics languages/toolkits: Python (strongly preferred; specifically with scipy, numpy, scikit-learn etc), R, SQL, SAS, SPSS, or Matlab
  • 2+ years of professional experience as a Data Scientist or equivalent analytics role
69

Senior Data Scientist Resume Examples & Samples

  • Minimum of 5 years of experience in building analytical data marts and data warehousing, or a minimum of 5 years building analytical models
  • Expertise in data tools, language and products used for data manipulation, data warehousing using one of these products/languages: Teradata, Hadoop, SAS
  • Strong SQL and basic Unix/Linux skills
  • Advanced programing skills in: SAS, R
  • Strong project management skills and detail oriented
  • Minimum of a master degree in computer science, statistics, data mining or related field
  • Solid understanding of the design and usage of MPP platforms
  • Experience with big-data
  • Strong independent self-driven professional
  • Experience with version control tools (svn, git and others) is a plus
  • Perl, Python, Java and C++ skills are a plus
70

Senior Data Scientist Resume Examples & Samples

  • Works with stakeholders to define business questions, success criteria, and model deployment plans
  • Checks in regularly with stakeholders during projects
  • Conducts exploratory data analysis and prepares visualizations summarizing key features of the data
  • Researches and adapts existing open source algorithms when possible, develops novel techniques when needed
  • Writes and optimizes complex SQL queries to build analytic data sets for both exploration and modeling
  • Develops reproducible information products and modular, instrumented software
  • Develops accurate models for prediction and inference
  • Provides guidance to software development engineers on production implementations
  • Develops program plans and road maps for Data Science
  • Experience distilling and presenting complex concepts to a business audience in a for-profit setting
  • Experience scoping and managing medium to large sized projects
  • Experience with different algorithm families and experience selecting, applying, and measuring model performance
  • Experience with machine learning and optimization techniques
  • Experience in data integration and transformation with SQL, statistical programming languages, and Linux command line tools
  • Expertise applying best practices in reproducible research and software engineering
  • Experience in all phases of the modeling pipeline on both desktop and distributed/cloud platforms
  • Expertise in predictive modeling using both supervised and unsupervised learning techniques. Must have experience in the following: generalized linear models, ensemble models, resampling methods, model validation and testing, dimensionality reduction, and clustering
  • Knowledge of experimental design
  • Experience with Spatial & Temporal Statistics
  • Demonstrated Exploratory Analysis and Visualization abilities
  • Solid experience at the Linux command line and with shell scripting
  • Experience automating applications in a distributed / parallel environment such as Hadoop, Spark, or H20
  • Advanced proficiency with at least one statistical computing language for data analysis, such as R or Python
  • Knowledge of and experience with recommender system algorithms and/or information retrieval
  • Experience working with unstructured and semi-structured data such as text and images
  • Experience practicing data science in retail and especially e-commerce settings
  • Experience teaching a quantitative subject or speaking in quantitative settings
  • Experience working in an agile methodology
  • Experience with the Google Could platform / Docker / Kubernetes
  • Experience with Spark and H20
  • Experience with Shiny / Jupyter / IPython
71

Senior Data Scientist Resume Examples & Samples

  • Partner closely with Product Management leadership to design, implement and analyze experiments that drive key product decisions
  • Proactively perform data exploration on user behavior with a focus on video analytics to discover future testing opportunities
  • Present your research and insights to all levels of the company, clearly and concisely
  • Research the best metrics to measure fan engagement
  • Lead the research and development of new experimentation methods and statistical techniques that could sharpen or speed up decision making
  • Relies on design of experiment and the scientific method to answer the “questions”
  • 3+ years relevant experience with a proven track record of leveraging analytics to drive significant business impact
  • Strong statistical knowledge and intuition - ideally utilized in A/B testing
  • Strong programming skills and a proven ability to learn new programming languages
  • Experience with distributed databases and query languages like Hive is a plus
  • Strong data visualizations skills to convey information and results clearly
  • Proficiency with a statistical analysis tool such as R or SAS
  • Ability to work independently and drive your own projects
  • Impactful presentation skills in front of a large and diverse audience
  • Innate curiosity about consumer behavior
  • A fan of movies and television is a strong plus
  • PhD or MS degree in Statistics, Mathematics, Physics, Operations Research, Econometrics or related field
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Senior Data Scientist Resume Examples & Samples

  • Bachelor’s Degree in business, engineering, computer science, marketing or related discipline from an accredited college or university
  • Minimum of 5 years of experience in productivity management, data science, or a closely related role
  • Advanced degrees (ME, EE or ChE) from an accredited university or college
  • Strong problem-solving and interpersonal skills; ability to convey technical concepts to audiences ranging from technicians to plant managers
  • Operating experience in power plants, preferably on boilers
  • Experience with Distributed Control Systems, preferably those common in power plants (e.g. ABB/Bailey, Emerson, Invensys, etc.)
  • Familiarity with data communication protocols such as OPC
  • Modeling experience with industrial systems
  • Experience applying neural networks to industrial processes
  • Familiarity with computer hardware & Windows-based software
  • Experience/familiarity with industrial process control systems
73

Senior Data Scientist Resume Examples & Samples

  • Develop analytics to address data science needs and opportunities
  • Work with data engineers on data quality assessment, data cleansing and data analytics
  • Minimum 2 year analytics development experience with high-level languages, such as R, Python, Perl, Ruby, Scala or similar scripting languages
  • Minimum 1 year hands-on experience in sourcing, cleaning, manipulating and analyzing large volumes of data
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Senior Data Scientist Resume Examples & Samples

  • 2) Work on fuzzy problem statements and iteratively refine the problem and solution
  • Bachelor’s degree in computer science, statistics and relevant fields, with 3-10 years of hands-on experience in delivering actionable Data Analytics deployed in production
  • Must have end-end hands-on experience in delivering & implementing Big data analytics in production. Must have skills, such as Synthesizing data, defining the problem, feature engineering, building the model, deploying the same in production
  • Experience working with large unfiltered data sets using distributed computing tools such as MapReduce, Pig
  • Knowledge and experience of statistical analysis tools such as R
  • Candidates aspiring for leadership role must have proven track record of 1-2 years of simultaneously working on multiple projects, with small teams of 3-4 data scientists and data engineers
75

Senior Data Scientist Resume Examples & Samples

  • Explore vast troves of social media, traditional media and offline data to extract actionable insights
  • Design systems, algorithms and models that predict future social performance
  • Analyze and understand social audiences to improve targeting efforts
  • Mine the social archive to better understand competitor performance
  • Build reports and dashboards that summarize and communicate opportunities across the business
  • BS or MS in computer science, computer engineering or mathematics
  • Professional background in statistics, machine learning or data mining
  • Deep knowledge of relational databases and SQL
  • Familiarity with data aggregation platforms like Domo, Tableau and Datorama
  • Knowledge of large-scale optimization methods, convex optimization, mixed integer programming, etc
  • Familiarity with social network schemas and APIs
  • Familiarity with statistical modeling and machine learning tools in R and Python
  • Familiarity with modern machine learning methods for regression and classification
76

Senior Data Scientist Resume Examples & Samples

  • Build Analytics and Reporting capabilities
  • PhD or MS Degree required
  • If candidate has PhD, candidate will have 2-3 years of relevant experience
  • Machine Learning and Data Mining or experience in a relevant role. (Particular areas of interests include supervised, semi-supervised or unsupervised learning, time series modeling, anomaly detection, graph or network analysis)
  • Familiarity with NoSQL databases
  • Analysis tools such as R
77

Senior Data Scientist Resume Examples & Samples

  • Developing demand forecasting models for our global cloud business by using statistical / machine learning techniques and building optimization models to support cloud capacity planning decisions
  • Working closely with other data scientists, forecasters and data engineers to develop demand forecasting models and optimization models that help capacity planning and deployment
  • Collaborating with Engineering, Product Managers, Operations, Sales & Marketing, Capacity Planning, and Finance to gather requirements of our business stakeholders, and to build forecasting and decision support models to improve efficiency
  • Presenting findings/insights regularly to forecasters, planners, stakeholders, and senior leadership including partners
  • Staying attuned to new statistical / machine learning / optimization techniques and bringing them into our cloud demand forecasting practice
  • 5+ years of work experience in quantitative forecasting with hands-on knowledge of statistical software tools and optimization tools such as R, SPSS, SAS, LP/NLP solvers
78

Senior Data Scientist Resume Examples & Samples

  • Creating new courses and/or enhancing existing courses
  • Providing data science training to corporations
  • Interviewing and providing feedback on applicants
  • Speaking at events and conferences
  • Writing articles and blogs
  • Assisting with instructor recruitment
  • Consulting on pro bono data science projects (e.g., with DataKind)
  • Providing in-house data science project expertise to specific companies
  • Authoring a book related to data science
  • Enrolling in data science classes
  • Working on open source passion projects
  • Part of a team that is transforming education
  • Three paid months per year to sharpen skills and pursue passion projects
  • Competitive compensation package
  • Opportunity to network and develop, both among Metis’ Data Science speaker community, as well as through Kaplan, the global educational company and parent company of Metis
  • Opportunity to work in different geographic locations (currently NYC and San Francisco)
79

Senior Data Scientist Resume Examples & Samples

  • Alongside senior members of the insights team, you will design and develop data mining, visualisation and analytics at the individual user level
  • You will develop and refine campaign segmentations and scoring models for use in direct, digital and social marketing activity
  • You will work with the myBBC team and wider M&A teams as they adopt advanced analytics insights
  • You will develop your skills and knowledge in data science, and keep up to date with the latest developments in the field
  • This role is suited to someone who is looking to take the next step in their career. You will have a numerical background and ideally several years’ experience of data analysis
  • You have a passion for and knowledge of advanced data analytics, digital media, broadcasting industries, and the BBC in particular
80

Senior Data Scientist Resume Examples & Samples

  • Bachelor Degree from an accredited university and 5+ years of experience; a Master's Degree is preferred. Prefer multiple areas of study: Information Systems, Operations Research, Engineering, Business Administration, Data Visualization, Data Science, and Visual Analytics
  • The selected candidate must be able to obtain a Secret security clearance
  • Visual Modeling Complex Problems—Ability to take the approach mentioned above and create a mathematical and logical model of the problem including uncertainty. Modeler needs to understand the logical relationships between the pieces of the problem, and must know how to mathematically and visually represent these relationships
  • Strong Linear Algebra Background—The analysis software used is based on arrays and matrix algebra. The Modeler must understand basic linear algebra, but it is helpful if he/she understands higher level linear algebra
  • Visual Programming—History with a graphical/visual programming interface
  • Optimization Background—Ability to determine the objective function and constraints within a complex problem and model the optimization
  • Familiarity with Tableau, Alteryx, Oracle Business Intelligence Enterprise (OBI EE), SQL Server, and ` Oracle Analytics
  • Analyst for complex Army or other DoD systems would be a plus
  • Worked in an agile development environment with short sprint deliveries (i.e., Scrum)
81

Senior Data Scientist Resume Examples & Samples

  • Gathers, analyzes, and interprets a wide variety of data
  • Plans data collection, and analyzes and interprets statistical data from surveys, experiments, studies, and other sources
  • Plans methods to collect information and develops questionnaire techniques according to survey design
  • Conducts surveys, evaluates reliability of source information, adjusts and weighs raw data, analyzes and interprets statistics, and organizes results
  • Conceive and prepare thorough, well-articulated tactical or strategic data science products (e.g. technical articles, visualizations, graphics, and intelligence reports) that summarize the methods and results of data science solutions
  • Design range of research projects, data collection and methodologies
  • Identify, retrieve, manipulate, relate and/or exploit multiple structured data sets from various sources
  • Identify problems to which data science can be applied and initiate appropriate solutions
  • Identify and appropriately evaluate a wide range of existing methods, models and algorithms in familiar domains for a variety of mission driven problems; recognizing the capabilities and limitations of methods
  • Conduct analysis of metadata
  • Exploit, fuse and use data and data sources
  • Identify and analyze anomalous data (including metadata)
  • Analyze data using appropriate tool set
  • Design and develop analytics
  • 9+ years of related statistical analysis experience
  • Familiarity with one or more types of quantitative data analysis. Social network or graph analysis preferred, but statistical, geospatial, modeling and simulation, or other accepted
  • Experience cleaning and manipulating data
  • Experience with predictive modeling
  • Experience with developing and implementing complex algorithms
  • Experience using statistical analysis tools (ie. R, RapidMiner)
  • Experience with analyzing large volumes of data using distributed processing architectures (ie. Hadoop)
  • Experience with Natural Language Processing (NLP)
  • Experience with Visual Basic and/or Python scripting
  • Familiarity with Intelligence Community, preferred
82

Senior Data Scientist Resume Examples & Samples

  • Master’s or higher in machine learning, a hard science, math, statistics or an engineering field, or equivalent work experience
  • Ability to quickly and efficiently adapt to new concepts
  • Demonstrated knowledge of statistical techniques
  • Ability to work collaborative with cross-function teams and business units
  • Demonstrated general business acumen; experience working in a real estate and mortgage related data industry a plus
83

Senior Data Scientist Resume Examples & Samples

  • Requires a BS in Computer Science, Data Science, Machine Learning or related technical fields, or equivalent work experience
  • Requires 4-8 years of related experience, as well as experience with mathematical programming, predictive analytics systems
  • Fluent in multiple application development languages at an expert level, R, Java, Scala preferred
  • Experience with various database platforms and environments, GreenPlum, Hadoop ecosystems, HAWQ, MongoDB preferred
  • Experience with various computer platforms and application environments, Linux required
  • Expertise in designing programs and processes
  • Experience with data management tools and environments, Informatica a plus
  • Constantly updating personal technical and business knowledge and skills and mentoring others to increase the knowledge and skills of the team
  • Project Management skills
  • Experience developing in an iterative Agile development environment
84

Senior Data Scientist Resume Examples & Samples

  • Research innovative data solutions to solve real market problems
  • Drive the creation of new models and capabilities that will leapfrog traditional bureau based modeling leveraging a wide array of data from both traditional and non-traditional sources
  • Conceptualize, analyze and develop actionable recommendations for strategic challenges facing the organization
  • Work with key stakeholders and understand their needs to develop new or improve existing solutions around data and analytics
  • Develop analytical approaches to meet business requirements; this involves translating requests into use cases, test cases, preparation of training data sets and iterative algorithm development
  • Manage data analysis to develop fact-based recommendations for innovation projects
  • Mine Big Data or unstructured data to tap new data sources and deliver insight into new and emerging solutions
  • Work with cross-functional teams to develop ideas and execute business plans
  • Remain current on new developments in data analytics, Big Data, predictive analytics, and technology
  • Advanced degree in a quantitative field (Statistics, Mathematics, Economics, etc.)
  • 10 or more years experience in modeling and predictive analytics with experience working with unstructured data
  • Experience in the credit risk industry
  • Excellent problem solving skills with the ability to design algorithms, which may include data cleaning, data mining, data clustering and pattern recognition methodologies
  • Strong skills in statistical analyses with abilities in advanced data management and statistical programming using SAS, R, STATA, Mathematica, Scala, Python, SQL, Hive, Impala, or other programming and statistical or mathematical packages
  • Experience in customer scoring, risk modeling, credit scoring, fraud detection, causal analysis, and pattern recognition
  • Ability to work cross-functionally in a highly matrix driven organization, at times under ambiguous circumstances
  • Experience with a range of big data architectures
  • Proven track record in defining strategies in the area of advanced data analysis and fostering knowledge exchange in large organizations
  • Proven research background, in industry work or academia
  • Ability to rapidly prototype solutions by combing background in data manipulation with mathematical modeling to derive insights
85

Senior Data Scientist Resume Examples & Samples

  • Master’s Degree in a “STEM” major (Science, Technology, Engineering, Mathematics) plus 1 year analytics development for industrial applications in a commercial setting OR Ph.D. in a “STEM” major (Science, Technology, Engineering, Mathematics)
  • Demonstrated skill at data visualization and storytelling for an audience of stakeholders
  • Demonstrated skill in data management with SQL, PostgreSQL, etc
  • Demonstrated skill in feature extraction and feature engineering
  • Demonstrated awareness of realtime analytics development and deployment
  • Demonstrated awareness of customer and stakeholder management and business metrics
  • Demonstrated skill at function in a team setting
86

Senior Data Scientist Resume Examples & Samples

  • Develop & implement models to support divisional strategy and business pillar initiatives
  • Develop advanced analytics models in order to maximize ROI, revenue and overall profitability
  • Leverage sound judgment, balancing analysis effort vs incremental improvement
  • Measure & communicate analytic results & impact of analytics models
  • Leverage extensive theoretical and practical knowledge of advanced analytic methods and algorithms, understanding their utility in different problem domains (sparse data, rare event detection, etc), evaluation methodologies and pitfalls, and stays on top of industry & academic developments
  • Coach & provide guidance to Data Scientists & Data Analysts
  • Leverage depth of experience in business, technical & analytical problem solving to support & coach other team members
  • Post grad in Statistics, Math, Comp Sci, Engineering or other related discipline (PhD preferred)
  • Minimum of 10 years' experience specifically in statistical/data analysis and data mining, predictive modeling, cluster analysis, optimization
  • Advanced Experience in Python, SQL, Java, R, VBA
  • Strong Knowledge of strategic marketing, data, audience targeting, segmentation, and customer analysis. Familiarity of vendors that operate in this space
  • Insurance or Financial Services industry experience preferred
  • Demonstrated experience exhibiting innovation and leadership in proposing new strategies and/or tactics based on analysis findings
  • Experience with Big Data platforms desired
87

Senior Data Scientist Resume Examples & Samples

  • Lead model development consulting engagements including interviewing appropriate business unit representatives, Senior and Executive Management to build models to stakeholder specifications and assist in model implementation
  • Design Econometric models to explore relationships between economic data and enterprise performance
  • Design models for Scottrade Enterprise as needed using, VaR, Monte Carlo and bootstrapping simulations
  • Lead in the development of detailed documentation of processes, procedures and performance tracking related to model development and application process
  • Deliver and convey model design, drivers, and results to assist assessment by validators and regulators. Evaluate assumptions, analyze data and present results of financial modeling
  • Produce model documentation in accordance to OCC 2011-12 and SR 11-7 regulatory guidance
  • Prepare and assist Lines of Business and Shared Services with model development projects and present results to Enterprise wide management
  • Prepare, analyze, and manage large data sets involving historical balances and incomes for statistical analyses
  • Support regulatory examinations and audits of the stress test modeling process and component models in conjunction with capital related research and analysis based on industry and peer data, and regulatory developments affecting the capital adequacy, planning and modeling process
  • Perform statistical research and literature review to provide insight into industry range of practice and support for various model choices
  • Research regulatory guidance and maintain enterprise policies and procedures around stress testing and model development
  • Support enterprise wide balance sheet forecasting and planning process as needed
  • Support the ongoing analysis of the bank and brokerage investment portfolios as needed
  • Coach and mentor members with the Risk Modeling department
  • Strong understanding of data segmentation, model development and validation, macroeconomic performance and credit loss forecasting techniques
  • Advanced knowledge of math terminology, econometric/statistical analysis and financial modeling techniques
  • Strong knowledge of micro and macro-economic fundamentals
  • Advanced knowledge of balance sheet modeling and database software
  • Intermediate knowledge of the wholesale and retail banking and brokerage businesses and the related models used in those businesses to manage risk
  • Basic knowledge of DFAST (Dodd Frank Act Stress Testing) and Capital Planning for a financial services organization
  • Basic understanding of financial and accounting principles, terminology and concepts
  • Basic understanding of fixed income terminology, product structures and financial instruments offered by banks
  • Ability to grasp complex information quickly and accurately
  • Strong attention to detail and process orientation in order to prioritize tasks
  • Proven ability to meet deadlines and drive results using multiple sources of information within short timelines
  • Advanced written and verbal communication skills in order to present findings to multiple audiences
  • Advanced level proficiency with Microsoft Excel
  • Intermediate level proficiency with Microsoft Word, PowerPoint and Outlook
  • Foster company success through a professional appearance, being courteous to customers and all Scottrade associates and by having a positive attitude
  • Master’s Degree in Mathematics, Finance, Economics, Accounting, or equivalent combination of education and experience required. PhD is preferred
  • 6+ years of experience with financial modeling/forecasting required
88

Senior Data Scientist Resume Examples & Samples

  • Collect, interpret, and disseminate data to allow for rapid product and content experimentation
  • Develop and foster services that will use data to create personalized and optimized experiences
  • Develop KPIs and measures of success in a cross-platform world
  • Communicate complex ideas in a clear, precise, yet accessible way to product, engineering, and editorial teams
89

Senior Data Scientist Resume Examples & Samples

  • Serve as the Data Guru of the company - i.e be aware of data streams captured in the company in any format (structured,
  • 8+ years of experience in Data Science and analytics fields
  • Experience with programming languages such as R, Python, or Scala
  • Experience in processing and analyzing Big data - i.e large scale data volumes, semi-structured and unstructured data and
90

Senior Data Scientist Resume Examples & Samples

  • *Telecommute (work from home) is available for candidates who live outside of a 50 mile radius of one of our four hub offices: Eden Prairie, MN, Franklin, TN, Wauwatosa, WI or Frederick, MD***
  • Partner with Fraud Operation leaders to design and integrate analytical strategies that enhance their Fraud detection capabilities and recovery efforts
  • Communicate results to business partners and clients
  • Partner effectively with business leaders and finance to demonstrate the effectiveness and impact of the analytical tools developed to support efforts to win new business
  • Oversee process to implement predictive models in the hardware / software supported by the business unit
  • Train business partners on how to most effectively incorporate model results into their work flow process
  • Bring these capabilities to Optum customers across markets: intersegment, government and commercial
  • Analytic responsibilities include data prep, choice of appropriate analytic and-or data mining approach, model development and documentation of process and results
  • Data scientist with 5+ years’ solid experience in predictive analytics and machine learning
  • Master’s degree in machine learning, computer science or applied mathematics / statistics with predictive model building expertise
  • 3+ years’ experience working with large volumes of data, extracting and manipulating large datasets using SAS and SQL
  • Strong hands-on modeling skills and strong programming skills using SAS. Communicate detailed requirement specifications for large scale implementations and-or deployments by software engineering teams
  • Self-motivated, capable of grasping analytical concepts and clearly explaining how analytical solutions can help customers reduce their healthcare claim costs
  • Excellent spoken and written English
  • Quick-thinker, fast learner, wide general knowledge, superb problem solver
  • Team worker, responsible, delivery-oriented
  • Develop and validate advance data mining tools, algorithms, and other capabilities to solve business problems
  • Exceptional ability to drive results through strong collaborating and influencing skills across different business segments
  • Collaborate with other research scientists and engineers to formulate innovative solutions to experiment and implement advanced data mining techniques
  • Analyze data covering a wide range of information from user profile to transaction history, and identify new risk patterns through data mining
  • Communicate complex concepts and the results of the analyses in a clear and effective manner through creative visualization
  • Experience with Enterprise Miner and / or R
  • Fraud and-or overpayment modeling experience
  • Knowledge of United Healthcare systems and businesses
  • Extensive experience working with health care claims data
  • PhD with 2+ years of experience
  • Working knowledge and understanding of medical coding systems, including ICD, CPT, DRG, etc
91

Senior Data Scientist Resume Examples & Samples

  • Support Principal Data Scientists to partner with Payment Integrity Operation management to identify the business requirements and the expected outcome
  • Collaborates with the data steward to gather information to be used for analytics and predictive model building purpose and to ensure the data meets the qualification and assurance requirements of the analyses
  • Provide on-going tracking and monitoring of performance of statistical models and recommend ongoing improvements to methods and algorithms that lead to findings, including new information
  • Masters or Ph.D. degree in (bio) statistics, applied statistics, applied mathematics, economics, or similar quantitative fields of study
  • 5+ years of experience of hands-on modeling skills and strong analytic programming skills using SAS tools, including SAS/BASE, SAS/STAT, and SAS Enterprise Guide
  • 5+ years of experience manipulating large datasets and using databases
  • SAS Enterprise Miner
  • Experience with health care claims data and Coordination of Benefits process
92

Senior Data Scientist Resume Examples & Samples

  • Lead a team of data scientists to discover insights and identify opportunities through the use of statistical, data mining and visualization techniques
  • Work closely with clients, clinicians, data stewards, and other business and technology leaders to frame problem definition and potential solutions
  • 5+ years of statistical analysis, quantitative analytics, and/or forecasting/predicting analytics
  • 2+ years of applying machine learning using distributed systems like Hadoop, Hive, Spark or similar libraries
  • 2+ years of experience with R or Python
  • Experience working in an Agile Software Development environment
  • Experience with healthcare data
  • External reputation in the industry
  • Experience with big data technologies like Hadoop, Hive, Spark, H2o and others
93

Senior Data Scientist Resume Examples & Samples

  • Lead the analyses of various structured or unstructured data sources for identifying actionable insights to enhance service delivery and improve Rx volume using Big Data Technologies (HDFS, Python, Hive, Pig, MapReduce and Machine Learning)
  • Develop supervised learning algorithms by utilizing Text Mining and Machine Learning for improving business processes
  • Support advanced analytical and data mining efforts which could include but not limited to clustering, segmentation, logistic and multivariate regression, decision/CART trees, neural networks, time-series analysis, sentiment analysis, topic modeling, and Bayesian analysis
  • Visualize, interpret, report, and communicate data findings creatively in a various formats and audiences using Shiny, Tableau, ggplot
  • Think creatively and work well both as part of a team and as an individual contributor. Keep pulse on new technologies (Apache Spark, D3) and solutions to solve business problems
  • Degree in Statistics, Applied Mathematics, Computer Science, Econometrics, Finance, Engineering, Operations Research, Bioinformatics, Information Systems, or related quantitative disciplines, with a minimum of five years of relevant experience (Bachelor’s required, Master’s or PhD’s preferred)
  • Expert in analytical tools like R, SAS, SQL, Hive, Pig
  • Expert in visualization tools like Shiny, ggplot, Tableau
  • Experienced in writing MapReduce jobs on HDFS, D3.js and scripting in Python, Linux
  • Experienced with using relational database management systems (Oracle, Teradata, SQL Server, DB2 etc.)
  • Facility with one or more data analytical methods such as regression, decision trees, experimental designs, support vector machines, machine learning and text mining
  • Other Tools required: Java, Scala, Apache Spark
  • Exceptional ability to communicate and present findings clearly to both technical and non-technical audiences
  • Excellent interpersonal and collaboration skills
  • LI-CK1
94

Senior Data Scientist Resume Examples & Samples

  • Develop complex but robust and easy to maintain optimization applications using ILOG/CPLEX
  • Work with the director of advanced analytics and business sponsors to identify,
  • Prioritize and plan out optimization projects
  • Serve as a subject matter expert for any enterprise initiatives that require
  • Nontrivial optimization
  • Partner with architects to set direction for maturing use of/retiring/adding technology components in the ESI environment
  • Provide technical guidance to projects/programs for complex components of a multiple technology suites
  • Lead efforts to develop standard practices, components, guidelines for use of complex optimization technology components
  • Work with teams to resolve urgent and high production level 4 incidents
  • Lead actions to determine root cause of problems and drive resolution
  • Work on special projects as assigned
  • Master’s degree in related field or equivalent work experience
  • 5 years experience using cplex/ilog to solve business problems
  • Technical: CPLEX/ILOG, SQL, Oracle Stored Procedures/Packages, UNIX/LINUX, Java
  • Financial: understanding of financial concepts of spread, discount rates, price point setting subject to various contractual obligations and business defined constraints. Practical knowledge of short-term forecast modeling
  • Ability to provide and implement technical solutions to a wide range of difficult problems
  • Strong customer service focus
  • Ability to lead discussions with all levels of the organization and provide balanced information of an idea or communication of an issue regardless of written or verbal
  • Demonstrated ability to prioritize work load and meet project deadlines
  • Adaptability and willingness to lean new tools and applications
  • Demonstrated ability to work collaboratively across project teams
  • Familiarity with health care or PBM industry is a plus
95

Senior Data Scientist Resume Examples & Samples

  • Lead the development of new Predictive models working with internal stakeholders from gathering requirements to delivery
  • Perform data mining by applying machine learning and supervised learning algorithms
  • Visualize, interpret, report, and communicate data findings creatively in a various formats and audiences using Tableau, ggplot
  • Think creatively and work well both as part of a team and as an individual contributor
  • Masters degree in Statistics, Applied Mathematics, Computer Science, Econometrics, Finance, Engineering, Operations Research, Bioinformatics, Information Systems, or related quantitative disciplines, with a minimum of 5 years of relevant experience
  • Expert in analytical tools like R, SAS, SQL, CPLEX and ILOG
  • Have hands-on experience developing predictive models using analytical methods such as regression, decision trees, support vector machines, Random Forests, Neural Networks
  • Have hands-on experience using relational database management systems (Oracle, Teradata, SQL Server, DB2 etc.)
  • Expertise in visualization tools like Tableau, ggplot is a plus
  • Expertise in Python, Linux is a plus
  • Experience using CPLEX and ILOG desired
96

Senior Data Scientist Resume Examples & Samples

  • Full-spectrum cyber operations, including (for example)
  • Active defense
  • Malware analysis
  • Red-team experience in cyber exercises
  • Information assurance
  • Cryptographic protocols
  • TS/SCI clearance with full lifestyle polyraph is required
  • Experienced software developer who enjoys hands-on systems building projects
  • Several years of experience with some of the following languages: C, C++, Java, Python, Perl, Ruby, assembler
  • Experience with some development tools such as IDEs (Eclipse, Netbeans, CodeWarrior, Visual Studio, Rational, etc.), source management systems (CVS, SVN, Git, etc.), testing tools (valgrind, etc.), debugging. In short someone who knows how to use the tools needed to accelerate development
  • Network experience of some kind. This can be at the low level (e.g., protocols - TCP, UDP, RIP, BGP, etc.) or at a higher level (socket programming, web services, etc.)
  • Must know open source tools. Linux experience preferred although familiarity with Windows and Linux is a plus
  • Experience with Java J2EE, Spring, containers (Weblogic, Websphere, etc), Tomcat
  • Experience with virtualization (VmWare, KVM, Xen, Docker, etc.)
  • Cloud experience (Openstack, Cloudera, AWS, etc.)
  • Large datasets and filesystems (Hadoop, etc.)
97

Senior Data Scientist Resume Examples & Samples

  • Analytics Consulting in collaboration with business teams identifying the relevant questions and defining the appropriate analytics methods
  • Modelling & Validating analytics scenarios by means of prototypes or pilot solutions
  • Developing business solutions to exploit analytics in order to move towards data-driven innovation in alignment with business priorities and key targets
98

Senior Data Scientist Resume Examples & Samples

  • Use predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from very large scale structured (mainly) and unstructured data
  • Develop software, algorithms and applications to apply mathematics to data, perform large scale experimentation and build data driven apps to translate data into intelligence
  • Solve variety of business problems and enable business strategy
  • Expand DCA web portal by developing complex queries using stored procedures and new graphics
  • Inform, influence, support, and execute business decisions and product design
  • Develop complex queries using stored procedures and similar methods
  • Design and develop automation scripts
  • Analyze and explore data to help discover hidden business insights in the data
  • Solid understanding of the machine learning and statistical approaches, and experience applying them
  • Experience with analytics packages (e.g., R, Scikit-Learn, MLlib, Matlab, Octave, Weka),
  • Passion for problem-solving, comfortable with ambiguity, and creative
  • Experience with large data sets and distributed computing (Spark/Hadoop) a plus
  • Experience integrating UI clients with complex Web-Services and REST APIs is a plus
  • Understanding of big data principles. Map-reduce experience is preferred
99

Senior Data Scientist Resume Examples & Samples

  • Work with large datasets and distributed computing tools (e.g., Hadoop, Hive and Pig) for analysis, data mining and modeling
  • Hands-on experience with Hadoop ecosystem tools (e.g., Hive, Pig, Sqoop) and some experience with NoSQL databases (e.g., MongoDB, Hbase of CouchDB)
  • Production experience with experimental design, statistical analysis, machine learning and predictive modeling (e.g., cross-sell, upsell, attrition, acquisition and look-alike models
  • Experience with UNIX tools and shell scripting
  • Experience using and implementing visualization tools like D3, Tableau or Qlikview
  • Highly motivated self-starter with experience producing high quality data deliverables and able to work independently and in a team environment
  • At least 2 years of big data analytics experience
100

Senior Data Scientist Resume Examples & Samples

  • Support the successful execution of all initiatives and projects of the Data Strategy and Innovation team
  • Work closely with the team VP and Sr. Manager, the department’s Creative Analytic Product Leads, and each of the individual brand’s research teams to understand the business, identify/prioritize needs, develop out comprehensive and efficient solutions, and translate / build into data delivery tools
  • Have a basic understanding of, and work closely with all types of data sets (e.g., metered measurement data, other syndicated data, survey data, social data) to be able to data mine, analyze, run forecasting models, create segments, etc. to ultimately drive insights and build new data delivery tools
  • Work with the team to facilitate a central repository and processing for all data, including standardized reporting and KPIs
  • Understand both Viacom’s business needs and existing data assets, in order to connect the dots and build data delivery tools that help in (not limited to the following)
  • 2+ years of experience (both hands-on and management) in working with/on the following: data science, statistics, big data, research (survey and measurement based), data platform architecture, BI, data visualization, data automation
  • Work with different types of data assets
  • Creative thinker and problem solver (being able to think outside the box, apply statistical know how to product innovation and application, connecting the dots and thinking holistically)
  • Effective verbal and written communication skills to be able to work successfully with key stakeholders, communicate with upper management, and drive enthusiasm and adoption of new products
  • Strong team player, and positive catalyst
101

Senior Data Scientist Resume Examples & Samples

  • With minimal guidance, use advanced statistical and computational methodologies to deliver insights and strategic opportunities to improve the quality, patient experience, and cost of healthcare
  • Establish scalable, efficient, and automated processes for large scale data analyses and model development, validation, and implementation
  • Proactively monitor and analyze complex systems to understand, diagnose, and continuously improve key performance indicators
  • Expertise in problem definition, i.e., able to translate business/research questions into analytical questions and translate analytical results into business/research solutions
  • Write statistical methodology and results for technical reports and publications
  • Manipulate, combine, and refine large databases to produce information suitable for analysis
  • Develop algorithms for data analysis and write computer code to implement them
  • Create graphics for data visualization and information display
  • Develop metrics and scorecards
  • Partner with senior leaders (SVP, EVP) across the organization to assess needs and define business questions
  • Able to take leadership of multiple projects concurrently and accommodate frequent interruptions and changing priorities
  • Able to influence senior leaders (SVP, EVP) to take action based on analytical insights
  • Creates timelines for project management with little or no assistance. Ensures successful completion of assigned projects on schedule, within budget, and in accordance with CHS standards and ethics
  • Ability to translate advanced methodologies and complex results for non-technical audiences
  • Conduct effective meetings with customers, including senior leaders
102

Senior Data Scientist Resume Examples & Samples

  • Use advanced quantitative techniques to solve problems for internal and external Caterpillar customers
  • Provide advanced analytic assistance to high-profile enterprise wide projects such as Strategic Improvement Projects
  • Practical Bent: be comfortable with doing something quickly and moving on, if need be, has to maximize impact rather than accuracy
  • Work closely with junior level Data Scientists to mentor and develop their analytical abilities and organizational knowledge
  • PhD/Masters degree, preferably in statistics, economics, computer science, engineering, mathematics, or a similar field with quantitative coursework
  • 6 - 10 years of relevant professional analytics experience utilizing quantitative analysis
  • Ability to work on increasingly more complex assignments and demonstrate strong leadership, initiative
  • Ability to communicate effectively
  • Work in multiple projects (multi task) efficiently and technically lead a team of junior analyst
  • Coach junior analysts technically on projects and work with them to deliver projects on quality on timely basis
  • Independently lead projects and proactively propose
  • Demonstrated experience in any of the areas like Marketing, Supply Chain, Manufacturing Analytics
  • Experience in using advanced analytical models and deep learning methods
  • Mandatory proficiency in s/w packages SAS, Python, R, Tableau or SPSS
103

Senior Data Scientist Resume Examples & Samples

  • Experience in core analytics methods (one or more of the following): Statistics (t-tests, ANOVA), variable reduction (FA, PCA), Segmentation/clustering techniques , Geographic cluster recognition and manipulation techniques, Predictive modeling: e.g. logistic regression, linear regression, Network analysis (location-allocation, travelling sales person, vehicle routing problem), Time series analysis: e.g. ARIMA, VAR, etc., Machine learning: e.g. LCA, Random Forest, neural networks, Spatio-temporal analysis, Time series analysis (ARIMA, VAR, etc.), Text mining & unstructured data analytics, Simulation: e.g. MC, dynamic, discrete event, Optimization: e.g. linear programming, heuristic
  • Familiarity with a broad base of analytics tools (one or more of the following):Data management: e.g. Excel, SQL, PostGRESql, Hadoop/Hive, Alteryx, Analytics platforms: e.g. SAS, R, RapidMiner, SPSS, Data visualization: e.g. Tableau, GIS toolkits (ESRI, Quantum GIS, MapInfo or similar), ESRI Network Analyst, RouteSmart, RoadNet or similar, GPS data analysis a plus, Programming and/or scripting exp.: eg. Python, C#, VBA, Java, Perl, etc
  • Experience in applied analytics for business problem solving: Eg. Extensive experience building analytical solutions for (one or more of the following), Pricing and promotional effectiveness, Delivery fleet consolidation, Loyalty program effectiveness, Network real estate reorganization, Customer segmentation and targeting, Delivery footprint/territory expansion (or reduction), Customer LTV maximization, Cost modeling of transportation & logistics operations, Churn prevention, Strong project management skills, Others a plus
  • Analytical and Conceptual thinking: A successful candidate will be able to conceptualize business problems and drive frameworks. The DS will produce leading edge business models and must be able to work in a hypothesis-based environment where inductive rather than deductive thinking is the norm
  • Engagement Management and Work with Case Teams:The successful candidate will have demonstrated ability to manage engagements, client relationships, provide “thought leadership” to teams and able to act as a full member of a BCG project team. They must own analytical modules from work planning to creating impact. He/she must provide perspective on work execution and process efficiency to analytics project lead. Strong presence, strong collaborator and leadership skills and ability to operate effectively in a matrix organization are a must
  • Client Relationship Management:The candidate with have a demonstrated ability to communicate effectively and professionally with clients, delivering impactful solutions and presenting work in a concise and thoughtful manner, while demonstrating technical expertise (fluency in English is required). Strong business focus with experience with 80/20 approaches
  • Analytics Innovation: Must be an autonomous self starter with a passion for analytics and problem solving. He/she will help build new Analytics service offerings that grow our portfolio of products and will captures proprietary content as well as analytics insights to the knowledge infrastructure. The candidate will support the creation of proposal/selling documents and provide perspective on relevant Analytics value propositions
104

Senior Data Scientist Resume Examples & Samples

  • Contribute to the analytical thought and help cultivate a data driven culture across the company
  • Perform ad hoc data mining and statistical analyses on complex marketing campaigns
  • Collaborate with the marketing strategy, media and modeling teams to develop practical segmentation strategies and targeting models for digital and omni-channel campaigns – from development through testing, validation and production implementation
  • Partner with market research to perform competitive analysis and identify gaps and opportunities in the marketplace that can be leveraged to devise new marketing programs
  • Partner with the marketing strategy and measurement teams to interpret implement the appropriate KPIs for various marketing programs and to evaluate and interpret the results of single and omni-channel strategies
  • Stay apprised of data and analytics trends and technologies and act as a key liaison to Marketing Engineering and IT to to ensure that requirements for integration, security, data quality, enrichment and cross-functional usage are addressed
  • Identify and perform "deep dive" analysis/data mining on special business topics for and with all major functional areas (Marketing ROI and optimization, forecasting, customer segmentation, etc.)
  • Provide senior level guidance to the acquisition marketing team on approach and methodologies as a subject matter expert
  • Ensuring accurate reporting, effective controls and the evolution of analytics services
  • Work closely with management team to prioritize business and information needs
  • 5+ years working with first and third party datasets
  • 5+ years working with both common relational and/or non-relational databases as well as Hadoop Ecosystem tools
  • 5+ years professional experience in marketing, product management, retail or related field in a quantitative role
  • 5+ years relevant experience in creating models utilizing statistics and/or machine learning, designing and implementing your own algorithms and data structures
  • Exposure to common web and digital media data sources
  • 2+ years in the telecom industry
  • Proven experience in operational analysis, data analysis and problem resolution type activities
  • Strong analytical skills with the ability to collect, organize and analyze significant amounts of information with attention to detail and accuracy
  • A capacity for translating ambiguous and competing business challenges into concise data-driven problems
  • Proficiency in constructing, publishing, and maintaining executive-level dashboards and visualizations which answer marketing questions to a variety of audiences
  • Ability to articulate and explain data in writing or verbally to stakeholders and executives in a clear and concise way
  • Strong problem solving and conceptual thinking abilities and intellectual curiosity to proactively uncover insights and trends within data
  • Masters/Advanced Degree. Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.)
  • At least 18 years of age. Legally authorized to work in the United States. High School Diploma or GED. Pre-employment background screen
105

Senior Data Scientist Resume Examples & Samples

  • Perform ad hoc data mining and statistical analyses on complex business problems
  • Lead the implementation, assessment, and standardization of toolkits for our data science, measurement science, insight management, and visualization teams
  • Research and work with technical teams to implement new and emerging technologies that will facilitate better data integrity, reliability, and enrichment for quantitative solutions
  • Provide senior level guidance to the data science and measurement science teams on approach and methodologies as a subject matter expert
  • 5+ years working with third party datasets
  • 5+ years working with common relational and/or non-relational databases and common web data and social data sources
  • Advanced knowledge of statistics and 5+ years developing statistics-based analytics reports
  • Proficiency in constructing, publishing, and maintaining executive-level dashboards and visualizations which answer technical questions to a variety of audiences
  • Experienced with Object Oriented Programming Language or Scripting Language
  • 2+ years experience in the telecom industry
106

Senior Data Scientist Resume Examples & Samples

  • Bachelors or Masters degree in Computer Science, Mathematics, Physics, Engineering, Statistics or other technical field. PhD preferred
  • Fundamental understanding of statistics, hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo
  • Experimentation design or A/B testing experience is preferred. * Strong coding abilities. Preference towards knowledge of one of the following open source languages: Scala, Java, C++ or C#. We use Python and C#
107

Senior Data Scientist Resume Examples & Samples

  • Verizon is seeking an exceptional Data Scientist to synthesize and leverage our massive dataset of Network events to improve reliability and improve customer experience. Understanding usage pattern and avoid disruption for customer’s service by proactively taking action will be most critical responsibility
  • Candidate will also be required to analyze UI usage pattern of operational users to identify opportunity to improve efficiency and creating different solutions to optimize usability
  • Candidate will work with cross-functional team members to identify and prioritize actionable, high-impact insights across a variety of core business areas. Will lead applied analytics initiatives that are leveraged across the breadth of our solutions for connectivity requirement for our customers. Candidate will research, design, implement and validate cutting-edge algorithms to analyze diverse sources of data to achieve targeted outcomes
  • As our data scientist, candidates will provide expertise on mathematical concepts for the broader applied analytics team and inspire the adoption of advanced analytics and data science across the entire breadth of our organization
  • Ph.D. or Master’s Degree in operations research, applied statistics, data mining, machine learning, physics, related quantitative discipline or work experience
  • Deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms
  • Experience delivering world-class data science outcomes
  • Ability to solve complex analytical problems using quantitative approaches with his/her unique blend of analytical, mathematical and technical skills
  • Passionate about asking and answering questions in large datasets, and able to communicate that passion to product managers and engineers. Have a keen desire to solve business problems, and live to find patterns and insights within structured and unstructured data
  • Accomplished in the use of statistical analysis environments such as R, MATLAB, SPSS or SAS
  • Experience with BI tools such as Tableau and Microstrategy
  • Comfortable with relational databases as with Hadoop-based data mining frameworks
  • Familiar with SQL, Python, Java and C/C++
108

Senior Data Scientist Resume Examples & Samples

  • Work closely with a research and computational scientists to identify and answer important R&ED scientific questions
  • Provide direct support to R&ED scientists to provide direction regarding data structure in support of project objectives
  • Responsible for ensuring the accurate, complete and timely collection, delivery and tracking of analytical information from translational R&ED, CRO or collaborating laboratories for analysis, reporting and presentation
  • Support the definition, delivery and utilization of R&ED, collaborator and partner laboratory analytical data management systems, processes and procedures
  • Work with R&ED study teams to develop R&ED information management plans that outline data capture, data flow, data queries, manual checks, and data listings needed to ensure data integrity
  • Participate in comprehensive data review activities in coordination with project and study teams
  • Work with computational biologists, computational scientists, biostatisticians and study scientists to resolve any data issues found during analysis
  • Make data, including interim data, available to R&ED department personnel as required
  • Must have proven ability to work effectively as a multi-disciplinary team member and lead partnering with laboratory and clinical scientists, data management and IT support functions to add value to drug discovery and early development programs
  • Bachelor’s degree in life sciences, computer sciences or a related discipline with at least 8 years or Master's degree in life sciences, computer sciences or related discipline with at least 6 years experience in biomedical data management, assay development, specimen data management or related discipline
  • Demonstrated proficiency with molecular biology concepts; and ability to support, develop and deploy laboratory and other research data management processes and procedures as they apply to complex, high dimensional data sets
  • Demonstrated ability to programmatically integrate, verify and report data according to specifications
  • Proven ability to work in a team environment with clinical personnel, study monitors, computational biologists, biostatisticians, programmers, and medical writers
  • Knowledge of FDA/ICH guidelines and industry standard practices regarding data management are helpful but not required
  • Detailed knowledge and experience in case report form design, central laboratories, programming databases, query resolution, data validation
  • Computer skills: detailed knowledge of at least one data management system (Oracle Clinical or Clintrial preferred), experience with SAS data sets and conversion procedures required; knowledge of MS Office program suite required
  • Knowledge of distributed database design and implementation, LAMP/ MySQL, etc. with capability to perform/direct/assess implementation of such databases
  • Strong understanding of LIMS systems and systematic, relational approaches to data integration and data processing workflows
  • Excellent skills in SAS and R programming and experience in additional computer languages such as Perl, Python, PHP, S-PLUS or Java (or C/C++)
  • Working knowledge of both Windows and Linux operating systems is required
  • Along with programming proficiency must have creativity, and show a strong capacity for independent thinking and the ability to grasp underlying biological questions
  • Must thrive in a complex, dynamic environment while adapting to dynamically changing priorities
  • Must have excellent written and verbal communication and presentation skills
109

Senior Data Scientist Resume Examples & Samples

  • As a member of cross-functional project teams, work with partners to identify and exploit analytical opportunities, including experimental planning, design and analysis
  • Apply rigorous statistical analysis, modeling, simulation, and predictive analytics to myriad experimental data sets and raise awareness of the value of various methodologies through education and evangelism
  • Propose new experiments and analytical processes to address novel questions that leverage Intrexon’s technology platform for strain, protein, and process engineering
  • Be a key partner in supporting Intrexon’s metabolic engineering and strain development, encompassing a broad array of microbial hosts
  • Prepare technical reports and make presentations to project teams, leadership, and other stakeholders
  • PhD (3+ years’ experience), MS (5+ years’ experience) or BS (8+ years’ experience) in physics, mathematics, statistics, genetics, engineering, bioinformatics, computer science or a related field
  • Experience in establishing a bioinformatics pipeline for strain engineering, protein engineering, statistical data analysis, and design of experiment approaches
  • Proven track record of accomplishments using applied machine learning and/or statistical techniques, preferably in the bio-industrial, life sciences, biotechnology, pharmaceutical, agriculture, or chemical field
  • Hands on experience in developing and implementing methods in descriptive, predictive, and prescriptive analytics & computational statistics
  • High dimensional data analysis (p >> n, dimensional reduction, clustering, etc.)
  • Statistical computing in R, Python, or MATLAB
  • Familiarity with database query performance optimization
  • Software development skills (functional vs object oriented design, version control, modular design)
  • High Performance Cloud Computing and Big Data computing architectures
  • Familiarity and applied experience in cutting edge techniques for machine learning
  • Understanding eukaryotic and prokaryotic biological systems including molecular and cellular biology
  • Ability to effectively communicate complex data and analysis to audiences with diverse technical backgrounds
  • Effectively portrays analysis conclusions in a graphical and/or interactive format
110

Senior Data Scientist Resume Examples & Samples

  • Build complex data sets from multiple data sources, both internally and externally
  • Build learning systems to analyze and filter continuous data flows and offline data analysis
  • Collaborate with cross-functional partners across the business
  • Collaborate with project teams to implement data modeling solutions
  • Combine data features to determine search models
  • Conduct advanced statistical analysis to determine trends and significant data relationships
  • Develop models of current state in order to determine improvements needed
  • Develop multiple custom data models to drive innovative business solutions
  • Drives the execution of multiple business plans and projects
  • Ensures business needs are being met
  • Interpret data to identify trends to go across future data sets
  • Promotes and supports company policies, procedures, mission, values, and standards of ethics and integrity
  • Provides supervision and development opportunities for associates
  • Research new techniques and best practices within the industry
  • Scale new algorithms to large data sets
  • Train algorithms to apply models to new data sets
  • Translate business needs into data requirements
  • Utilize system tools including (MySQL, Hadoop, Weka, R, Matlab,ILog)
  • Validate models and algorithmic techniques
111

Senior Data Scientist Resume Examples & Samples

  • Perform hands-on data exploration and modeling work on massive data sets
  • Architect, develop, and maintain data analytics platforms that visualize data and drive business insights that can be translated into product strategies and marketing decisions
  • Spend time researching state of the art modeling techniques and implement them
112

Senior Data Scientist Resume Examples & Samples

  • Gather, clean, report, and interpret data rapidly and thoughtfully.​ Ingest terabytes of data, identify the critical signal in all that information, and then act on that signal to drive millions in growth or savings
  • Perform ad hoc analyses using statistics, machine learning, and data mining techniques with whatever tool makes sense for the problem. Don't be limited to just one tool or approach. Let the problem, and not your past, drive the analysis
  • In conjunction with above, perform self-directed ad-hoc analysis to identify drivers of business outcomes. Your manager's job shouldn't be to give you tasks. It should be to give you direction, and then provide whatever support you need to get there
  • Report findings, recommendations, and conclusions resulting from analysis. The more people understand an insight, the more useful it is. Your insights can make a huge difference at Overstock, but only if they're understood
  • Use and support database applications. Understanding our data, and how it's used, is, not surprisingly, critical to data science
  • Follow legal policies as directed
  • SAS
  • Aster SQL-MR
  • Bayesian Statistics/Probabilistic Modeling/Programming
  • Visualization
  • NOSQL platforms
113

Senior Data Scientist Resume Examples & Samples

  • Analyze advisor, investor and economic trends that impact sales/marketing/business performance and recommend ways to improve outcomes
  • Create the capability to study and analyze structured and unstructured data, data from multiple internal and external sources to enable pattern seeking and analysis
  • Create a pattern recognition process by identifying and integrating internal and external sources of information, analytical tools, and data management and manipulation tools
  • Perform complex data manipulation and analytics, while working with business functions to identify and to respond to complex technical and business problems
  • Develop statistical forecasting models
  • Interpret and communicate analytic results to analytical and non-analytical business partners and senior managers
  • Degree in Statistics, Mathematics, Machine Learning, Operations Research, Computer Science, Econometrics or related field. Master’s degree highly preferred
  • 4+ years relevant experience with a proven track record of leveraging analytics and large amounts of data to drive significant business impact
  • Passion for learning and innovating new methodologies in the intersection of applied math / probability / statistics / computer science. Proficient at translating unstructured business problems into an abstract mathematical framework
  • Expertise in predictive analytics/statistical modeling/data mining algorithms. Must have knowledge/experience in some/all of the following: Multivariate Regression, Logistic Regression, Support Vector Machines, Bagging, Boosting, Decision Trees, Lifetime analysis, common clustering algorithms, Optimization, Stochastic Processes
  • Ability to make intelligent approximations of mathematical models in order to make them practical and scalable
  • Proficiency in at least one statistical analysis tool such as R, SAS, and SQL
  • Experience with distributed databases and query languages like Hive/Pig/Sawzall and/or general map reduce computing is a plus
  • Knowledge of common data structures and ability to write efficient code in at least one language is a plus (preferably Java, C++, Python, or Perl)
  • Exceptional interpersonal and communication skills, including the ability to describe the logic and implications of a complex model to all types of business partners
114

Senior Data Scientist Resume Examples & Samples

  • Note that work samples will be requested, and applicants might also be tested as part of the interview process
  • Advanced expertise in data analytics and scientific methodology and a passion to apply those scientific talents to improve the performance of government
  • Advanced creative skill in translating complex insights from the research literature into applied, feasible interventions, as well as fluency in explaining complex topics with authority to busy practitioners
  • Advanced expertise in creatively determining which analytic approaches and computing techniques are most appropriate for a given data situation
  • Advanced expertise and creativity in visualizing, analyzing, and communicating insights from data
  • Advanced expertise with at least one statistical programming language, such as R, Python, Stata, SAS, or similar
  • Advanced expertise in handling complex datasets, including importing, merging, and reshaping datasets, as well as handling duplicates, discrepancies, missing entries, and other quirks of large administrative data
  • Expertise, as demonstrated by advanced coursework or equivalent experience, in at least three (3) of the following: machine learning; econometrics; design and analyses of experiments; or data visualization and interaction
  • Experience using and developing APIs and other open data structures
  • Proficiency in distributed computing. ​
115

Senior Data Scientist Resume Examples & Samples

  • A passion to identify and solve real business problems using large volume of data
  • Ability to work in a multicultural team environment
  • Ability to gather, prepare and manipulate large datasets
  • Ability to create, train and implement Machine Learning models
  • Persistence and willingness to learn and apply new techniques/new tools constantly
  • Functional knowledge of one of the analytical tools (e.g. R, Matlab) or one programming language (Python, Java, C++)
  • Creativity in using available tools and out-of-the-box thinking to provide viable solutions to problems
  • Ability to demonstrate findings using various visualization tools such as Tableau by creating compelling visualizations
  • Excellent presentation skills to explain complicated analytical solutions to a non-technical group of people
  • Strong statistical, analytical and problem solving skills
  • Experience in managing large data sets
  • Familiarity with creating and training Machine Learning algorithms (e.g. Recommendation engines, forecasting, clustering, classifiers etc)
  • Proficient in analytical methods & tools (e.g. SAS, R, Matlab), experienced in data visualization (e.g. Tableau)
  • Ability to dive into complex systems/issues and business problems, and able to quickly grasp/define ambiguous or theoretical situations
116

Senior Data Scientist Resume Examples & Samples

  • Master degree in Statistics, Math, Computer Science, Operations Research, CME or similar quantitative majors with a strong academic record
  • 3-5 years of work experience, preferably as a data scientist or in highly technical and analytical role
  • Experience with object-oriented programming languages such as Java and C++
  • Strong communication and presentation skills to deliver findings of analysis and to explain complex statistical concepts to a non-technical audience
  • 5+ years of work experience, preferably as data scientist or in highly analytical role
  • Work closely with product managers and analysts to understand key business questions that need answering
  • Lead complex analysis and predictive modeling projects to drive understanding of the game network and enable key decision-making
  • Translate findings into actionable recommendations to leadership for product enhancement
  • Work closely with engineers to integrate prototypes of data models into the production environment
117

Senior Data Scientist Resume Examples & Samples

  • Enjoy using your creative and quantitative skills to find new insights from big data
  • Build complex data systems that make people say, wow that is cool!
  • Stay on the cutting edge of Big Data and Data Science
  • Collaborate with an international team to deliver global solutions
  • Bachelor’s Degree in Data Science, Statistics, Computer Science, Math, or similar quantitative field
  • 3+ years of professional experience with machine learning, statistical analysis, predictive modeling, time series analysis, and/or customer segmentation
  • Strong data discovery and analysis skills
  • Experience with big data using technologies like Hadoop, Spark, NoSQL and/or traditional relational databases
  • Experience with statistical software packages &/or machine learning tools (R, Matlab, SPSS, SAS, SciPy, Mahout, Torch)
  • Experience with a variety of relevant languages (Java or C#, Scala, Python, Pig, SQL) preferably on Linux
  • Business experience with common machine learning models (Decision trees, Linear models, Naïve Bayes, Neural Nets)
  • Business experience with data visualization (ggplot2, d3)
  • Familiarity with Agile/Scrum
  • Familiarity with software as a service, API development
  • Familiarity with standard software development practices (source control, unit testing, code reviews, automation, performance monitoring)
  • Master’s or PhD in a relevant quantitative field
118

Senior Data Scientist Resume Examples & Samples

  • Leading development of machine learning models/predictive analytics techniques leveraging both repeatable patterns in data and discovering new that reduce cost, increase performance, reliability and or endurance in semiconductor products
  • Ability to quickly understand challenging business problems, find patterns and insights within structured and unstructured data
  • Ability to access, analyze and transform large product lifecycle and process data in the semiconductor/fab manufacturing industry
  • Ability to think critically about the relationships of different metrics measured and process steps to land the right features for a given model
  • Challenge current best thinking, test theories, evaluate feature concepts and iterate rapidly
  • Experience with advanced data mining, predictive modeling algorithms, developing data models, reinforced, supervised and unsupervised learning methods such as SVMs, linear classifiers, Markov models, Bayesian networks and clustering techniques strong plus
  • Experience/proficiency in at least one compiled/object oriented programming language e.g. Java/C++
  • Experience with big data technologies such as Hadoop, MapReduce, Mahout, Hive, Pig etc. and parallelization tools in enterprise Big Data Platform stack, technologies and ecosystem is a strong plus
  • Advanced degree, Masters or PH.D in Computer Science, Statistics, Applied Math, Engineering with an emphasis on Machine Learning
  • Highly motivated, team player with an entrepreneurial spirit and strong communication and collaboration skills, self-starter with willingness to learn, master new technologies and clearly communicate results to technical and non-technical audience
  • Fluency with understanding and learning the Semiconductor/wafer data, fluency learning and adapting to the existing tools Yield explorer and others, with very entrepreneurial personality trait, not afraid to play, hands on coding and iteratively problem solve
119

Senior Data Scientist Resume Examples & Samples

  • Create predictive models for various business processes like supplier risk, payment or transaction risk, relationship discovery, catalog search optimization (e.g., matching)
  • Work with other data scientists and cross-functionally with product managers and engineering teams to deliver predictive models from concept to product
  • 4-7 years of experience
  • Hands-on experience in statistical analysis and predictive model development (classification, clustering, logistic regression and/or neural networks, etc.) and machine learning; knowledge of statistical programming languages (e.g., R, SAS, Model Builder) a plus
  • Be an iterative and quick thinker – you deliver preliminary results fast and then iterate over time
  • M.S. or Ph.D. in statistics, mathematics, computer science (data mining or machine learning focus), economics, bioinformatics, or another quantitative scientific field
  • Experience in user interface and data visualization a plus
  • Experience with Hadoop based technologies such as MapReduce, Hive, Pig, HBase, Cassandra, noSQL databases
120

Senior Data Scientist Resume Examples & Samples

  • Lead predictive modeling work based on defining and gathering requirements, including collaboration with internal stakeholders for end-to-end delivery
  • Machine learning practices for data mining, including supervised learning algorithms
  • Advanced analytical work (e.g. logistic and multivariate regression, decision trees / CART, neural networks, time-series analysis, Bayesian analysis, segmentation, clustering)
  • Data visualization, reporting and presentation to all levels of audience (e.g. using Tableau or ggplot)
  • Master’s degree in quantitative discipline such as Applied Mathematics, Statistics, Engineering, Bioinformatics, Econometrics, Operations Research, Computer Science / Information Systems
  • Minimum of 7 years’ relevant experience
  • Expert in SAS, SQL, R and/or similar analytical tools
  • Experience using CPLEX and ILOG strongly desired
  • Experience in development of predictive models using neural networks, decision trees, support vector machines, regression or similar methods
  • Experience using relational database management systems such as SQL Server, DB2, Oracle, Teradata
  • Expertise in Python, Linux and Tableau, ggplot or other data visualization tools is a plus
121

Senior Data Scientist Resume Examples & Samples

  • Develop models for characterizing audience and their online behavior on various devices
  • Develop models for forecasting supply of inventory across various dimensions - publishers, devices, country etc
  • Develop models for optimizing bidding across various supply sources
  • Develop scalable algorithms for optimizing ad delivery
  • Support engineering and product management with data science focused products
  • Develop scalable algorithms for ad-delivery optimization and traffic quality
  • Implement machine learning algorithms for audience segmentation
  • Communication of scientific results in terms of presentations, UI visualizations, and automated reports, etc
122

Senior Data Scientist Resume Examples & Samples

  • Design optimization algorithms for ad targeting and delivery at ad-serving time
  • Constantly experiment and improve the relevancy of the ad-delivery optimization system
  • Develop YuMe’s overall technology platform and offering
123

Senior Data Scientist Resume Examples & Samples

  • Build a statistics driven ad optimization system, working closely with the product team
  • Ph.D. in Math/Statistics/Computer Science or equivalent with an emphasis on programming
  • Strong understanding of Algorithms, Data Structures and Machine Learning / Data Mining
  • Experience with math/statistics tools such as R or MATLAB
  • Solid understanding of yield management
  • Solid understanding of control theory and Markov decision processes
  • Solid understanding of numerical optimization (linear, integer, nonlinear, and dynamic programming)
  • Solid understanding of forecasting
  • Previous experience in digital ad serving optimization a huge plus
  • Previous experience in digital advertising and ad targeting a big plus
  • Previous experience in web analytics a big plus
  • Experience with Machine Learning / Data Mining open source tools, preferably in Java (e.g., Weka)
  • Experience with Hadoop Map/Reduce, Hadoop streaming, Pig, or Hive
  • Ability to work in a fast paced, test-driven collaborative and iterative programming environment
  • 7+ years of experience; majority of experience should be in the online advertising industry
124

Senior Data Scientist Resume Examples & Samples

  • Work with management, data scientists and software developers on projects related to technology and architecture of digital media systems including identifying and implementing products and services for Web based and Mobile delivery
  • High and low-level responsibilities including analytics coding for prototype and production systems
  • Provide hands-on support for production systems and upgrades, which often occur outside normal business hours
  • There are no supervisory responsibilities associated with this job
  • MS in Computer Science or equivalent relevant experience
  • 5+ years of data analytics / mining / machine learning / analytics coding
  • Familiarity with statistical methods required. Practical familiarity with similarity computations, algorithms and clustering, item and user similarity, large data sets and statistical analysis tools. Practical experience with Spark, Tableau, Mahout/Hadoop systems, Hive, Pig, Kafka, optimization and tuning considered a strong plus
  • Experienced with sequencing algorithms and theory (e.g. Markov chains, Bayes Networks) for media and entertainment applications such as content sequencing. Familiar with statistical analysis languages (e.g. Mathematica, Matlab, R, SparkR). Familiar with machine learning and IOT
  • Experience with Search and Content Recommendation services. Understanding of Search and Recommendation service features including classifications, machine learning, trending, data visualization and structuring recommendations
  • Experience with natural language processing (NLP) including supervised and unsupervised learning valuable
  • Familiarity with Social Media API level interactions and with contemporary social media site access and social graph navigation valuable
  • Development experience in B2B application infrastructure including organizing large data sets, New/NoSQL, XML, XSD, XSLT a plus
  • Experienced in Java, Python, Scala, R, JSON/XML essential
  • Must have demonstrated track record of rapid prototyping of system components as part of new system architecture
  • Practical experience on architecture and deployment of software components into cloud based infrastructures, e.g. Amazon Web Services. Experience with cloud management services, caching, scale-out and use of cloud APIs useful
125

Senior Data Scientist Resume Examples & Samples

  • ILOG/CPLEX programming to develop optimization applications, balancing robustness and ease of maintenance
  • Subject matter expertise for all nontrivial optimization initiatives
  • Help identify technology components to be added / retired / better utilized, partnering with data architects
  • Develop standard and best practices and guidelines for use of complex optimization technology components
  • Incident resolution and root cause determination
  • 5+ years using ILOG / CPLEX
  • Master’s degree in a quantitative, finance or computer science related discipline
  • Technical expertise: SQL, UNIX / LINUX, Java, Oracle Stored Procedures (in addition to ILOG / CPLEX)
  • Financial concepts expertise: price point setting, spread, discount rates, short-term forecast modeling
  • Strong customer service focus and communication skills to present to all levels of technical and non-technical audiences
  • Experience in the healthcare industry is a plus
126

Senior Data Scientist Resume Examples & Samples

  • Use text mining and machine learning to develop supervised learning algorithms for process improvement
  • Lead analyses using Big Data Technologies (e.g. Python, machine learning, HDFS, Hive, Pig, MapReduce) and structured or unstructured data sources to improve service delivery
  • Advanced analytical work (e.g. logistic and multivariate regression, decision trees / CART, neural networks, sentiment analysis, topic modeling, time-series analysis, Bayesian analysis, segmentation, clustering)
  • Knowledge of advanced analytical methods such as machine learning, text mining, decision trees, support vector machines, regression
  • Degree in quantitative discipline such as Applied Mathematics, Statistics, Engineering, Bioinformatics, Econometrics, Operations Research, Computer Science / Information Systems (Master’s / PhD preferred) with a minimum of 5 years relevant experience
  • Expert in Tableau, ggplot or other data visualization tools
  • Experience with MapReduce programming on HDFS or D3.js, as well as Python or Linux
127

Senior Data Scientist Resume Examples & Samples

  • Thoroughly understand the company's usage data
  • Support ongoing business analyses as required to inform management decisions
  • Develop algorithms and predictive models to solve critical business problems for Salesforce, including the development of smarter CRM applications
  • Develop tools and libraries that will help us to surface deeper more valuable insights faster
128

Senior Data Scientist Resume Examples & Samples

  • Understand customer business use cases and be able to translate them to analytical data applications and models with a vision on how to implement a solution
  • Clearly communicate the business and technical benefits of analytics and visualization to both business and technical audiences
  • Support subsequent business units in developing and implementing Tableau server dashboards and other analytical solutions
  • Manipulate, aggregate and derive useful information from data stored across many sources and different databases
  • Ability to apply data analysis to solve a business problem that has a real impact to customers
  • Excellent team player
  • Must be self-motivated, results driven, and able to work with minimum supervision
  • 5+ years of experience in the applied analytic space
  • 5+ years of programming skills & experience in Java, C++, R, Perl, or Python
  • Strong understanding of algorithms and advanced data structures
  • 3+ years of advanced experience with Hadoop (preferably HDP)
  • Advanced understanding of Hadoop framework and data structures
129

Senior Data Scientist Resume Examples & Samples

  • Lead several projects of moderate to complex nature w/ minimal. feedback / rework from manager/mentor of project
  • Leads large project teams and/or high priority efforts to actionable, outcomes oriented results
  • Proactively creates, teaches and checks work, which may include analysis, results, project outcomes, programming, etc. of less senior staff for reasonability and accuracy
  • Contributes to dept infrastructure (e.g. training, recruiting, client relations)
  • Negotiates with others to achieve deliverables on time and within budget
  • Identifies the right issues to be communicated, the appropriate audience, vehicle and time
  • Defines and frames complex multidimensional issues and develops time tables/processes for decision making
  • Translates needs, issues, and ideas into effective strategies and action plans
  • Formulates specific implementation plans in partnership w/ constituent groups (internal and external, National and across Regions) and evaluates the effectiveness of actions/programs implemented
  • Develops creative alternative solutions
  • Recognizes opportunities by making a connection between seemingly unrelated information
  • Minimum eight (8) years of work experience
  • Bachelor's degree and seven (7) years of work experience OR a master's degree and five (5) years of work experience preferred
  • Knowledge of health care industry preferred
  • Familiarity with Kaiser Permanente health care system preferred
130

Senior Data Scientist Resume Examples & Samples

  • Development Process – Follow defined software development process. Perform documentation, design, code, and defect reviews
  • Four year degree in Engineering, Science, Mathematics or related field from an accredited college or university
  • Experience in working with Hadoop, MapReduce, Hive, HBase and other big data technologies
  • RDBMS and/or knowledge on NoSql platforms
  • Familiarity and experience with software deployment and support
131

Senior Data Scientist Resume Examples & Samples

  • Influences stakeholders to make product/service improvements that yield customer/business value by effectively making compelling cases through story-telling, visualizations, and other influencing tools
  • Strong background in Machine Learning - Time series, unsupervised classification, decision tree, logistic and multiple regression; Operation Research - Optimization; Statistics - Parametric, Non-parametric tests, Multivariate, PCA, Factor analysis
  • Proven ability to translate business and product questions into analytics projects
  • Expert in querying and analyzing data using R, Python, SAS, SPSS, Scope, SQL, Scope Effective communication skills and the ability to work collaboratively with stakeholders, executives and subject matter experts
132

Senior Data Scientist Resume Examples & Samples

  • Participate in use case feasibility discussions and transalte business idea/ business problem into analytics use case
  • Perform complex data analyses, segmentation, and profiling
  • Develop and maintain complex analytical models and algorithms
  • Build sophisticated predictive/prescriptive models to generate insights about customers, products, sales, and operations for specific use cases. Create and maintain the master data file and model predictive summary
  • Explain insights from analyses and point out implications, risks, and usability constraints
  • Write model technical documentation
  • Prepare and deliver presentations detailing results of analytics
  • Own the model development from end-to-end, starting with data collection to incorporating adjustments post-pilot
  • Provide support as needed to maintain and update models running in production environment
  • Develop trusted partnerships with business stakeholders and subject matter experts
  • Develop and command a deep understanding and working knowledge of Pacific Life’s suite of IT systems, data sources, and data models
133

Senior Data Scientist Resume Examples & Samples

  • Map our user journey and increase the understanding of our customers by developing profiles and segments with internal and external data sources
  • Track KPIs and create standard reports and dashboards to analyze marketing performance across digital and traditional channels; work with cross-functional teams to set targets and measure performance
  • Collaborate on the development of multi-touch marketing strategies across targeted segments, assuring optimized marketing investment and performance across all owned channels, working closely with CRM, digital marketing, social, and ecommerce teams
  • Build predictive models to help assess segment/cohort performance, and provide actionable insights for marketing and product teams; work with the data engineering team to productionalize those models
  • 4+ years of experience in related work experience, ideally at a tech company and/or ecommerce environment
  • Strong understanding and experience using SQL
  • Experience working with large data sets in a Hadoop environment
  • Experience using Tableau, Python, R, SAS, Stata, Excel, or similar tools
  • Advanced Statistical modeling skills
  • Experience with Adobe, Google Analytics
  • Good grasp on website and mobile measurement (A/B testing, campaign attribution, media mix modeling, SEO)
  • Ability to synthesize data from multiple sources to drive actionable insights; a proven influencer with excellent communication skills
  • Bachelor/ Graduate degree in Computer Science, Engineering, Analytics, Marketing, Statistics, Math, or Economics
  • Previous experience leading a team is a plus
134

Senior Data Scientist Resume Examples & Samples

  • Working experience in data analytics
  • Strong knowledge and working experience in Hadoop, preferably with formal training/certification from reputed institutes
  • Ability to understand algorithms and translate them into MapReduce/Spark framework and support different analytics projects across the data science locations
  • Ability to develop abstract interfaces to reduce the steep learning curve of Big Data Technologies
  • Ability to assess/evaluate and recommend right platform and tools
  • Collaborate with researchers in the ACS's corporate global lab supporting ACS businesses to create innovative products & solutions
  • Leverage knowhow and domain knowledge of Honeywell experts to define, design and develop intelligent algorithms to operate on large data sets
  • Develop and deploy data science based analytical algorithms
  • Build a strong data science group by teaming and collaborating with other team members
  • Bachelor's or Master's in Computer Science, Statistics, or other relevant degree
  • Experience working in data analytics atleast for a year
  • Experience working with distributed computing tools such as MapReduce, Pig, Spark
135

Senior Data Scientist Resume Examples & Samples

  • Working on client engagement teams in carrying out both reactive and proactive data analysis of large volume of structured data involving a wide range of database management systems and financial platforms
  • Working with clients, fraud investigators, internal and external auditors, lawyers and regulatory authorities in sensitive and sometimes adversarial situations
  • Working in our specialist forensic technology data analytics labs and onsite to help clients leverage knowledge from their data through the application of advanced analytics
136

Senior Data Scientist Resume Examples & Samples

  • Predict future customer behavior and business conditions (Machine Learning, Predictive Modeling)
  • Algorithmically drive our business actions to optimize performance under real world constraints (Optimization, Exploration/Exploitation, Bandit Algorithms)
  • Understand the impact our pricing and promotional campaigns have on our customers and business (Experiment Design, Hypothesis Testing, Causal Inference)
  • Shape our products and activities to improve the customer experience and business impact
  • Investigate and design data driven solutions for challenging business problems
137

Senior Data Scientist Resume Examples & Samples

  • Interface with product management, engineering and research to perform complex deep dives and evaluate optimization prototypes
  • Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions
  • Use data mining, model building, and other analytical techniques to develop and maintain customer segmentations
  • Make recommendations for new metrics, techniques, and strategies to improve marketing campaign targeting and measurement in the future
  • Work with engineering to enable the appropriate capture and storage of key data points
  • Design, implement, and support platforms that provide business teams ad-hoc access to large datasets (eg data visualization tools for non-tech business users)
  • Be connected and influential within the Amazon Business Intelligence community
  • 5+ years of professional experience in business analytic, business intelligence (BI) or comparable consumer analyst position
  • Experience managing large and complex data sets (in the order of millions or billions of records)
  • Bachelor's degree in Math, Finance, Statistics, Engineering, or related discipline
  • Strong SQL and Excel expertise to access and transform data into insights
  • MBA or Masters degree in an analytic field is desired
  • Knowledge and direct experience using BI reporting tools. (Tableau, OBIEE, Business Objects, Cognos, MicroStrategy, etc.)
  • Experience with statistical modeling, dataming and machine learning (R, Python, SAS, etc.)
  • Experience in Online Advertising Experience is preferred. (experience in Paid Search is ideal)
138

Senior Data Scientist Resume Examples & Samples

  • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
  • An MS/PhD in CS, Machine Learning, Operational research, Statistics or in a highly quantitative field. PhD strongly preferred
  • 4+ years of industry experience in predictive modeling and analysis, predictive software development
  • Experience handling terabyte size datasets
  • Publications or presentation in recognized Machine Learning and Data Mining journals/conferences
139

Senior Data Scientist Resume Examples & Samples

  • Collaborate on the development of new advertising products by evaluating the business and competitive landscape, understanding customer needs and value drivers, and crafting high impact growth strategies for the business
  • Analyze and extract relevant information from large amounts of Amazon's historical business data; Then applied revenue management, machine learning and data mining techniques to create data driven models and solutions
  • Lead the development of quantitative models necessary for evaluation and implementation of novel monetization strategies
  • Surface data-driven insights and recommendation to capitalized on novel revenue opportunity and expand the portfolio of adverting clients
  • MS (PhD preferred) in Computer Science, Machine Learning, Operations Research, Applied Mathematics or in another highly quantitative field
  • 3+ years of hands-on experience in machine learning, data mining and/or quantitative analysis
  • Fluency in a modeling language such as Python scientific computing libraries, Matlab, or R
  • PhD in Computer Science, Machine Learning, Operations Research, Applied Mathematics or in another highly quantitative field
140

Senior Data Scientist Resume Examples & Samples

  • Demonstrated advanced ability to use Microsoft Excel
  • Ability to translate complex, technical findings into an easily understood narrative (i.e., tell a story with the data) in graphical, verbal, or written form
  • Preferred Master’s or PhD in behavioral sciences with strong demonstrated background in statistics and research design
  • Have minimum (5) five years of analytic experience
  • EEOD Experience
  • Human Resources Experience
  • Intelligence Community experience
141

Senior Data Scientist Resume Examples & Samples

  • 5+ years' experience as a data scientist
  • Strong machine learning and predictive analytics skills
  • The ability to lead a team and communicate with C-level executives
  • Working knowledge of statistics and stats packages like R or Matlab A scripting language (Python, Ruby, etc.)
  • SQL and working knowledge of relational databases Visualization tools (examples: Tableau, Looker, MicroStrategy, etc.) and/or custom Visualization scripting (examples: D3, Highcharts, R Shiny, etc.)
  • A/B testing experience
142

Senior Data Scientist Resume Examples & Samples

  • PhD or Master’s degree in Mathematics, Statistics, Computer Science, Operations Research, Physics or other quantitative discipline like Financial engineering
  • 2+ years of AML or fraud analytics experience in the financial services industry
  • 2+ years of experience in building machine models in R, Python or SAS , using techniques such as Random Forest, ANN, SVM, logistic regression
  • Hands-on expertise with SQL databases such as Oracle is required
143

Senior Data Scientist Resume Examples & Samples

  • Efficiently execute well-defined, discrete analytic tasks based on the needs of the client, as communicated by the client management team
  • Work with client management team and our customers to define and take ownership of scope, intermediate deliverables, and timelines around larger-scale analytic deliverables
  • Work with application management team, and where necessary, other members of the customer analytics team to efficiently execute larger-scale analytic deliverables and operationalize the results
  • Mentor junior team members regarding methodology definition, efficient usage of technology stack, and customer communication
  • Identify recurring problems and bottlenecks that might be improved through upgrades to our software product, new technologies in the analytics team’s infrastructure, or further research into statistical methodology
  • BA/BS or MS in Computer Science, Mathematics, Statistics, Physics, or other STEM field
  • Minimum 3 years of professional work experience in a data analysis role (experience energy or utility industry data is a huge plus)
  • Comfort with producing customer-facing deliverables and coordinating efforts across multiple teams
  • Significant prior experience framing and conducting analyses in relational database environments (e.g. Oracle DB, MySQL, PostgreSQL, MSSQL) and/or through spreadsheet-based tools
  • A passion for and curiosity about new big data analytics technologies and methodologies
144

Senior Data Scientist Resume Examples & Samples

  • Providing thought-leadership in the implementation of analytical solutions
  • Communicating with team members, project management and research statisticians/data scientists to understand requirements and strategically implement solutions into robust software functionality
  • Writing prototype and eventually productionizing code and completing analysis to understand and improve our understanding of the ID Graph as a whole
  • Researching and implementing hybrid probabilistic-graph algorithms
  • Identifying opportunities for improvement in data cleansing, manipulating, and processing within existing software applications and frameworks
  • Consistently striving to produce the most accurate ID profiles to be used as the foundation for all Oracle Data Cloud products and processes
  • 3+ years of experience in a field related to data science or MS in statistics, computer science, analytics, or data science
  • Experience working with big data tools (Spark, Hive, Hadoop, etc.)
  • Experience with cloud infrastructures (Amazon Web Services, Microsoft Azure, Google Cloud)
  • Experience with one or more programming languages (Python, R, Scala, etc.)
  • Experience with graph-based analytics a plus
  • Experience in digital ad-tech a plus
  • Comfortable working in Linux environments
  • Interest in mentoring data scientists and desire to act as a mentor to up and coming data scientists is a plus
  • Collaborative, positive attitude with desire to work in a demanding,
145

Senior Data Scientist Resume Examples & Samples

  • Work with product managers and engineers to define, design, and develop solutions to customer problems using data and analytic techniques
  • Design experiments, test hypotheses, and build models/prototypes
  • Leverage tools, processes and procedures to create, manipulate, and manage very large data sets
  • Communicate results of the analyses in a clearly and effective manner to stakeholders
  • Work with engineering, user experience, and IT teams to transition prototype to product and/or service offering
  • Develop, document, and transfer to Honeywell businesses technology that enables new product and service offerings
146

Senior Data Scientist Resume Examples & Samples

  • Knowledge of advanced linear and non-linear regression techniques, customer segmentation, Bayesian methods, decision trees, clustering, factor analysis and principal components analysis
  • SAS programming skills, including SAS/BASE, SAS/STAT, SAS/MACRO and SAS SQL, familiarity with PROC MIXED or GLIMMIX a plus
  • Solid technical database knowledge (Oracle, Teradata, data modeling) and experience optimizing SQL queries on large data
  • Hadoop experience, including HIVE, PIG, Sqoop, Hbase. Experience with custom Map Reduce, R and Mahout in Hadoop a strong plus
  • Passionately analytical and curious with strong out-of-the-box thinking
  • Able to develop and present conclusions based on analysis to senior executives
  • Outstanding written, verbal, and presentation skills
  • Able to work effectively within an fast changing environment, tight deadlines, priority changes and multiple constituencies
  • Experience working in a sales and/or retail environment a plus
147

Senior Data Scientist Resume Examples & Samples

  • Work with clients to gather and refine specific business problems and scenarios and document analytical solution requirements
  • Create and maintain documentation of technical requirements including use cases
  • Define the data requirements for specific business problems and Identify sources of data in consultation with business clients (e.g., in-house data store/warehouse, external data mart, etc.)
  • Identify and resolve data/information gaps for meeting business objectives/goals including data quality issues and sources (data feeds, the master data, etc.), and identify training and validation datasets as appropriate
  • Build multiple analytical models to solve specific business problems using commercial or open source toolsets
  • Work with stakeholders to establish minimum levels of performance criteria for model selection
  • Work with Business clients to Validate/Test subset of model(s) and obtain approval for models that achieve specified business goals
  • Report Analytical results in a variety of creative visual formats that appropriately provides insights to business clients
  • Define technical requests for Technical Specialists to perform, such as detailed data linking or parallel processing requests
  • Ability to write production level code
  • Exposure to Big Data technologies (Hadoop, HDFS, Pig, Hive, etc.)
  • Familiarity with NoSQL databases (e.g., HBase, Cassandra, Mongo DB)
  • Experience with Tableau or other data visualization tools
  • Experience working with customers (consulting experience a plus)
  • Diverse data set experience
  • Experience with PMML
  • Experience with Python or Scala
148

Senior Data Scientist Resume Examples & Samples

  • 3+ years of experience using advanced analytical techniques to solve business problems
  • 1+ year(s) of analytics team or project leadership experience including responsibility for planning, resource management, and final deliverables
  • Intermediate / Advanced querying and scripting skills in SQL Server
  • Advanced Excel and R or Python skills with a focus on formula development and model building
  • Proficiency in data management and processing with a commitment to understanding trends and underlying factors in data
  • Demonstrated background in quantitative analysis, especially concepts related to statistical and/or machine learning analysis
  • Ability to multi-task and communicate effectively across teams in a deadline-driven atmosphere
  • Experience with cloud-based computing, Python, UNIX, and/or digital marketing is preferred but not required
  • Numerate degree in Computer Science, Mathematics, Management Science, or relevant area (graduate degree preferred)
149

Senior Data Scientist Resume Examples & Samples

  • Analyze architecture, relationship between systems, and systems flow of end-to-end designs
  • Build analytical solutions and models by manipulating large data sets and integrating diverse data sources
  • Perform ad-hoc analysis and develop reproducible analytical approaches to meet business requirements
  • Apply machine learning and statistical techniques to large data sets to find actionable insights
  • Research new modeling techniques and evolving technologies
  • Guide others to assess system usage trends and identify potential performance constraints with inter-system designs
  • Develops and reviews project plans, identifies issues, resolves issues, and communicates status of assigned projects to users and manager
  • Present results and recommendations to senior management and business users
  • Lead & manage data augmentation, clean up and data quality issue resolution
  • Responsible for providing line of sight to data quality and gaps where issues need to be addressed
  • A/B testing of hypothesis and models
  • Write scripts to develop programs that improve processing of access requests
  • Reduce security threats with dependable & reliable security tools & software applications
  • Evaluate how security impacts the design & development process of reliable networks
  • Provides operational support for Hadoop based Big Data Platforms
150

Senior Data Scientist Resume Examples & Samples

  • The ideal candidate should have an MS (Ph.D preferred) in a quantitative areas such as Math, Operations Research, Quantitative Physics or a similar engineering field
  • Practical knowledge of programming skills (C, C++, C#, SQL, or equivalent)
  • Deep experience for unlocking information in big data to improve business insight
  • Experience with using machine learning algorithms to solve problems
151

Senior Data Scientist Resume Examples & Samples

  • Apply statistical concepts and techniques to analyze experiments and user behavior
  • Present findings and recommendations to key decision makers at various management levels
  • MBA or Masters / Ph.D. in Science, Mathematics, Applied Physics, Statistics, or Operations Research from a reputed institution
  • Field of graduate education - Mathematics, Statistics, Science, Engineering, Operational Research, Computer Science or Management Science
152

Senior Data Scientist Resume Examples & Samples

  • Join Apple’s Applied Machine Learning Team as a Data Scientist. We are looking for a candidate who can leverage/develop innovative machine learning and data mining technologies, for solving novel and diverse sets of problems
  • Candidate should have a strong background and experience in machine learning and information retrieval
  • Experience communicating with diverse teams including data scientists, engineers, product managers, and executive management
  • Proven track record of delivering high quality analytics insights and solutions
  • Deep understanding, analysis, and mining of large corpora of structured and semi-structured data
  • Knowledge and experience managing and analyzing global data
  • Strong experience with Big Data (min 2 years of hands-on experience working on TB to PB scale datasets)
  • Strength in Machine Learning, Statistical Modeling, Data Mining, Pattern Recognition, Information Retrieval, Natural Language Processing, or Search Ranking
  • Experience using all these ML techniques: clustering, regression, classification, graphical models, mixture models, topic models, and matrix factorization
  • Self driven individual who can take a high-level problem and see it to completion
  • Knowledge of distributed computing solutions and ability to leverage them towards gaining faster insights from data
  • Excellent communication and team promotion skills
153

Senior Data Scientist Resume Examples & Samples

  • Work with and analyze large amounts of data. Interact with functional experts, at all levels, to understand business issues, challenges and identify new opportunities. Collaborate with users and team members to provide accurate estimates for assigned tasks. Work individually and as a team member to ensure stability of company production systems
  • Perform various statistical analyses using data drawn from diverse sources to map and identify genuine trends and relationships
  • Develop and devise advanced analytical analysis, methods and tools for design, quality, production and engineering departments
  • Reviews and recommend changes to existing business analysis procedures and methods by incorporating data analysis techniques
  • Present results to management, including data-driven business recommendations and alternatives. Provides accurate timely status reports/scoreboards, delivering assignments on-time with a high level of quality
  • Provide expert perspective on modeling approach, technique and tools in resolving the business problem
  • Help identify, assess, and document potential data sources and flows, and analyze existing data warehouses to determine relevance trends to business needs
  • Research latest technique and tools to continuously enhance the discipline
  • Must have strong problem solving and analytical skills
  • Must have solid project management experience
  • Must have an innate desire to learn and continually improve
  • Knowledge of ISO 9001 Quality Systems
  • Knowledge of design techniques, tools, and principles involved in production of technical plans, blueprints, drawings, and models desired
  • Knowledge of practical application of engineering science and technology; including applying principles, techniques, procedures, and equipment to the design and production of various goods and services desired
  • Minimum 5 years hands-on experience in mathematical/statistical model buildings
  • United States citizenship required
  • Ability to effectively establish rapport and develop effective relationships
  • Ability to effectively communicate orally and through written documents
  • Ability to link customer needs and business processes
  • Required mathematical/statistical skills include ANOVA, design of experiments (DOE), statistical process control (SPC), regression analysis (linear and logistics), multivariate data analysis, non-parametric models, decision trees, and pattern recognition
  • Knowledge of statistical software MINITAB, JMP, SAS
  • Proficient programming skills in Visual Basic, Matlab, C++, C#, or Java
  • Excellent SQL knowledge, advanced skills in scripting/programming
  • Advanced experience in creating Access databases and Excel Reports, using modules, forms, macros, formulas, VBA
  • Initiative; Persistence; Integrity; Critical Thinking; Time Management; Judgment and Decision Making; Effective Communication; Attention to Detail; Adaptability/Flexibility; Effective Problem Solving
154

Senior Data Scientist Resume Examples & Samples

  • Writing prototype code in Python, Scala, Hive, and Spark to understand and improve our understanding of the ID Graph as a whole
  • Researching and implementing hybrid probabilistic-graph algorithms on massive amounts of data
  • Independently optimizing and tweaking code and the cloud environment
  • Understanding the business asks and requirements for the Identity Graph then provide thought-leadership in the implementation of analytical solutions
  • Collaborating with other team members and data scientists to brainstorm solutions
  • Collaborating with engineers to build scaled and supported ID Graph products
  • Communicating effectively across teams to explain the solutions put in place and the implications on the business
  • 3+ years of experience in a field related to data science or MS in statistics, computer science, or other data science field
  • Experience with cloud infrastructures (Amazon Web Services)
  • Experience with one or more programming languages (Python, Scala, etc.)
  • Comfortable working as part data scientist and part computer scientist / data engineer
  • Comfortable working independently to optimize code and cloud environments to complete analyses
  • Exceptional problem solving skills with unrelenting focus on practical business implications
  • Self-sufficient in ability to take a problem and answer the question at hand as well as take it three steps further
  • Collaborative, positive attitude with desire to work in a demanding, fast-paced, and dynamic work environment
155

Senior Data Scientist Resume Examples & Samples

  • Run sophisticated models to measure the effectiveness of digital ad campaigns
  • Evaluate predictive models used to build targeted audiences for digital and mail campaigns
  • Design and conduct custom research to answer key client questions
  • Present findings to a variety of audiences—including ad agencies, analysts, media planners, marketing managers and executives
  • Consult with clients to identify opportunities to grow their business through analytics
  • Collaborate with internal teams (Research & Development, Go to Market, Operations, Product, and Technology) to continually improve our targeting and measurement solutions
  • Identify and lead strategic analytic initiatives
  • Bachelor’s or Master’s degree in a quantitative discipline—such as economics, engineering, mathematics, operations research or statistics
  • Professional expertise in marketing analytics
  • Familiarity with retail companies and their data assets
  • Competency with big-data tools—such as SQL, Python, R, SAS
  • Mad communication skills—especially around displaying data and leading audiences from complex situations to simple, logical conclusions
156

Senior Data Scientist Resume Examples & Samples

  • Identifies, proposes, and implements enhancements to production processes based on simulations, optimizations, statistical analysis, or other process modeling
  • Develops and implements rate forecast models to be used in a production environment for sample ordering and selection
  • Leads innovation throughout the department and implements solutions that reduce cost, improve quality, or increase efficiency of existing products
  • Creates, maintains, and improves long term forecast models used as inputs to the budgeting and budget reconciliation processes
  • Develops an expert level knowledge of multiple large Oracle, Netezza, and SQL Server databases
  • Writes and maintains complex SQL queries on large databases
  • Utilizes tools such as Python, Tableau, SAS, etc. to perform complex data analysis
  • Establishes and maintains benchmarks around service performance and process capability
  • Creates data visualizations to provide management insight to complex business problems
  • Serves on various interdepartmental teams seeking to propose, evaluate, and implement new initiatives
  • Works as an integral member of the Sampling Department in a time-critical production environment
  • Undergraduate degree in economics, business, mathematics, statistics, engineering, survey methods or related fields
  • 3+ years’ experience working with any one of the following: optimization, simulation, data mining, or forecasting
  • Proficiency with SQL, Toad, Oracle, SQL Server or other relational database software including manipulation of large data sets and table creation and indexing
  • Proficiency in Python coding including experience with SciPy, NumPy, & Pandas packages
  • Knowledge of statistical tests and procedures such as ANOVA, Chi-squared, Correlation, Regression, Student t-test, Time Series
  • Expert in at least two of SAS Programming, Enterprise Guide, Enterprise Miner, or Forecast Server
  • Demonstrated success and effectiveness working in a time-critical production environment
  • Excellent leadership skills and proven ability to work independently as well as part of a team
  • Critical thinking and creative problem solving skills
  • Strong planning and organizational skills
  • Proficiency in Excel, Access, PowerPoint and Word
  • Master’s degree in Data Science, Mathematics, Operations Research, Statistics, or related field
  • Knowledge of data collection and research methodologies and/or experience with syndicated data
  • Experience with Tableau, SpotFire, Business Objects, or related data visualization software
  • Knowledge of process improvement methodologies such as Lean, Six Sigma or CMMI
  • Familiarity with R and R Studio
157

Senior Data Scientist Resume Examples & Samples

  • Collaboratively create and manage projects, from timeline creation to project completion, managing expectations with manager and customer
  • Plays a key role in analytical projects from beginning to end; including developing analytical plan, running analyses, and summarizing results
  • Compiling and delivering documentation material such as power point slides for methodology questions and/or frequently asked questions; supporting basic client service duties as needed; and participating in team projects and staff meetings
  • Uses statistical methodologies to analyze the data
  • Participates in team projects and staff meetings
  • Bachelors degree in Statistics, Social Science, Operation Research, or other hard sciences (e.g. Engineering, Computer Science, Biology, Physics)
  • Masters degree in an above mentioned field- preferred
  • 3-5 years experience
  • Broad industry knowledge
  • Proficient in Python, SAS, SPSS, R, Stata or other statistical packages
  • Strong statistical and logic skills
  • Exceptional aptitude for data analysis
  • Visual basic programming
  • Intellectual curiosity and persistence to find answers to questions
  • LI=MJ1
158

Senior Data Scientist Resume Examples & Samples

  • Understanding data, data aggregation, Data treatment
  • Establishing Methodologies, Predictive model building, Hypothesis testing
  • Synthesizing results, preparing presentations and presenting them to Business partners
  • Masters Degree in Statistics, Mathematics, and Economics, Operations Research,or MBA(with Engineering in Bachelors) or BTech or similar research oriented quantitative discipline
  • Atleast 7 years of experience in analytical role
  • Experience in SAS/R/Python and SQL
  • Experience working with very large databases (500+ GB)
  • A working knowledge of RDMS, including table structure and metadata, and database tools
  • Experience working with very large databases (500+ GB).Working knowledge of RDMS, including table structure and metadata, and database tools
  • Working knowledge of a financial institution's organizational areas and/or the mutual fund industry is desirable
  • Good Communication skills and should be able to explain his/her ideas / thought process clearly
  • Keeps up-to-date with leading-edge developments as related to profession and/or industry
  • Willingness to work in a Team and as an Individual to garner best results
  • Serves as a technical resource for others. Has in-depth experience in the area
  • Professional development growth opportunities through in-house classes and over 150 Web-based training courses
  • An educational assistance program to financially help employees seeking continuing education
  • Medical, Life and Personal Accident Insurance benefit for employees. Medical insurance also cover employees dependents (spouses, children and dependent parents)
  • Life insurance for protection of employees’ families
  • Personal accident insurance for protection of employees and their families
  • Personal loan assistance
  • Employee Stock Investment Plan (ESIP)
159

Senior Data Scientist Resume Examples & Samples

  • Master’s degree in Computer Science, Math, Physics, Engineering, Statistics. PhD preferred
  • Expertise to develop data models, and the ability to create reports using Power BI
  • 5+ years of experience manipulating large data sets through statistical software (ex. R, SAS)
160

Senior Data Scientist Resume Examples & Samples

  • Build out an analytics framework for the understanding, monitoring and optimization of Lead Generation conversion, enabling test and learn capability and the implementation of Next Best Actions
  • Work with stakeholders in wider marketing team to ensure Paid Media marketing activity is intelligence led and designed to learn
  • Build an analytical approach to marketing spend allocation
161

Senior Data Scientist Resume Examples & Samples

  • 3+ years of experience using Excel for business analysis
  • Experience with or serious interest in learning SQL
  • Deadline management skills with solid oral & written communication and a rigorous quality assurance ethic
162

Senior Data Scientist Resume Examples & Samples

  • Work on all stages of data science projects from understanding data to implementing the solutions into products and service offerings
  • Develop strong relationships with business, manufacturing and supply chain team members by being proactive, displaying a thorough understanding of the business processes and by recommending innovative solutions
  • Provide data modeling, mining, pattern analysis, data visualization and machine learning solutions to address manufacturing and integrated supply chain needs
  • Promote data science methods and processes across functions
  • Attend industry conferences to stay current on industry trends, challenges, and potential market opportunities
  • Work with our businesses and infrastructure teams to develop a strategy that will clearly outline how our enterprise platforms can enable business growth & productivity by seamlessly combining structured and unstructured data into a single, self-service analytical environment
163

Senior Data Scientist Resume Examples & Samples

  • A strong understanding and interest in machine learning, natural language processing, or information retrieval
  • Desire to solve challenges new problems at the intersection of user experience and computational algorithms
  • Strong engineering skills, preferably in Java/C/C++ and preference for candidates with prior search experience
  • Demonstrated ability to work as part of a small, focused team and complete critical milestones under pressure
164

Senior Data Scientist Resume Examples & Samples

  • Develop highly scalable E2E architecture for hosting and operationalizing ML models
  • Build text analytics solutions by applying advance techniques for entity extraction and topic clustering
  • Enable high frequency low-cost experimentation to empower MSEG scenarios
  • Guide the team on developing the systems for high stability, fast development, low development cost, and low maintenance cost
  • Help shape vision, design, architecture and scale for the ML platform
  • Provide technical leadership to other team members
  • Strong expertise and experience on design and development of platforms, or metric systems with a track record of shipping multiple releases
  • Extensive software design and development skills/experience
  • Experience deploying and managing machine learning models is a big plus
  • Expert knowledge in Cosmos, TLC, Azure ML, .NET, C#, C++
  • Ability to drive sound architecture, design, and implementation through hands-on development
  • Database expertise and online service are strong plusses
165

Senior Data Scientist Resume Examples & Samples

  • Design , develop and manage our data science platform for creating personalized experience for our consumers across all digital communication touchpoint
  • Make the most appropriate use of advanced methods from the fields of statistics, data mining, or machine learning (regressions, decisions trees, neural networks, K-means, survival analysis)
  • Measure yourself and your success along clear metrics mapped on the planed contribution of your deliveries to the goals of the organization
  • Communicates at all level of the organization to ensure understanding and adoptions of the insights
  • Dealing with the issues faced by our Business internal clients, and working/communicating effectively with/to them at different levels (e.g. strategic or operational) are for you an essential and enjoyable part of your Data Scientist task
  • Strong affinity and willingness to build sustainable, reusable, practical analytical applications
  • Strong organizational skills and workflow planning, deliver within time, budget and resource specifications, ability to prioritize
  • Strong intuition, remarkable ability to be creative and develop new, uncharted analytical solutions to business problems
  • Working language is English
  • MS degree or PhD in a numeric / statistical discipline (mathematics, stats, physics, economics, operational research) or a track record that proves the same
  • A minimum of 6 years professional experience in data science and analytic role , 2 – 4 years focus on CRM / consumer profiling / recommendation systems
  • Excellent knowledge of digital landscape, and applications of predictive analytics in real-time recommendation and personalization across channels
  • Experience with large amounts of consumer data / Big data
  • Experience on data aggregations, data models, and operationalization of data mining algorithms, in to production systems . e.g. PMML
  • Excellent knowledge in applied statistics, distributions, statistical testing, data mining and machine learning algorithms
166

Senior Data Scientist Resume Examples & Samples

  • Analyze, design, develop, test, troubleshoot and document complex data systems that may involve one or more of the following: data mining, predictive models, machine learning, data-drive decision making and other related concepts
  • Providing technical input to internal teams regarding data discovery, planning and processing
  • Anticipate business needs and work proactively to improve data management processes and collaborate with developers to implement improvements
  • Keep current with outside advancements in data science techniques and inject developments as appropriate
  • Minimum 10 years of industry experience for Master’s candidates or 7 years for Ph.D. candidates
  • Minimum 7 years of data science experience in industry for Master’s candidates or 5 years for Ph.D. candidates
  • Experience in creating and applying advanced statistical methods and machine learning algorithms such as: data mining, regression, clustering, simulation, scenario analysis, neural networks and decision trees
  • Experience creating simple, concise visualizations of data and presenting to stakeholders through visualization software such as Tableau, PowerBI, Periscope, or other similar software
  • Minimum of 7 years of programming experience (C, C++, Java, Python, R)
  • Minimum of 7 years of experience with relational databases and SQL
  • Experience with statistical or computational mathematics tools (SAS, R, Jmp, Matlab)
  • Experience with web services such as AWS, Redshift, S3, and/or Spark connecting to data using API’s
  • Experience connecting and analyzing data from multiple business applications(SAP, SFDC, IBM Cognos)
  • Systems engineer or reliability engineering experience
  • Ability to work in a global collaborative team environment
  • Excellent verbal and written communication skills in English
  • Master’s degree or Ph.D. in a relevant technical discipline (Mathematics, Engineering, Computer Science, Statistics or a similar field)
167

Senior Data Scientist Resume Examples & Samples

  • Develops and codes software programs, algorithms, mathematical approaches and automated processes to solve business problems
  • Uses analytical rigor and statistical methods, machine learning, programming, data modeling, simulation and advanced mathematics to analyze large amounts of data, recognizing patterns, identifying opportunities, posing business questions and making valuable discoveries
  • Researches new ways for modeling and predictive behavior for large scale projects.​
  • Generate and test hypotheses, designing experiments to answer targeted questions of advanced complexity
  • Define data needs, evaluate data quality, and extract/manipulate data in a “Big Data” environment
  • Documents projects including business objective, data gathering and processes, leading approaches, final algorithm, detailed set of results and analytical metrics. Interface closely with business teams to understand/define key challenges, data requirements, and domain knowledge/models
  • Interprets and communicates insights and findings
  • Coaches and mentors less experienced associates
  • Consistently demonstrates regular, dependable attendance & punctuality
  • Experience with Neo4J or other GraphDB
  • JAVA programming experience desired
  • Bachelor's Degree in Applied Statistics/Mathematics/Economics and Operations Research or Computer Science and 6 or more years of progressively complex experience (Master's Degree preferred)
  • 5 years advanced statistical techniques such as predictive statistical models, customer profiling, segmentation analysis, survey design and analysis, and data mining
  • Advanced proficiency in working with large datasets in a 'Big Data' environment, preferably in retail/e-commerce or other customer facing industry
  • Experience with extraction and manipulation of relational databases (SQL)
  • Programming and analytical experience in major analytics software packages (SAS, R, Python, SPSS, Matlab, Pearl, Linear, etc)
  • Ability to generate quick, iterative solutions to a business problems, from online marketing to merchandising
  • Experience with unstructured data sets, cloud based architectures, and deployment frameworks for machine learning algorithms (e.g. Hadoop, Hive, Hbase, Mahout, etc.)
  • Ability to take initiative and deliver tangible results under deadlines
  • Communication Skills: Excellent written and verbal communication skills. Ability to read, write, and interpret business and technical documents. Ability to communicate complex information
  • Advanced statistical knowledge, including experience with application of statistic to predictive analytics, probabilistic modeling, and unstructured text analysis
  • Works under minimal supervision with wide latitude for independent judgment. Projects are large in scope with a high level of complexity
168

Senior Data Scientist Resume Examples & Samples

  • Develop requirements for developers to include outcomes in software solutions
  • Conduct training and knowledge transfer in data science
  • Work closely with clients, data stewards, and other business and technology leaders to frame problem definition and potential solutions
  • 5+ years of Machine Learning, Artificial Intelligence, Predictive Analytics experience (inclusive of academic experience)
  • 2+ years of incorporating ML & Al concepts into solution development in a professional capacity
  • 2+ years of professional experience with one or more of the following Machine Learning and Cognitive technologies: IBM Watson, SAS, Amazon ML, Google Cloud ML, Azure ML Studio
  • 2+ years hands on experience in applying core Machine Learning methodologies: Regression, Classification, Clustering, Matrix Factorization, Predictive Analytics, Natural Language processing, Decision trees, Support Vector Machines, Neural Networks/ Deep Learning
  • 2+ years of experience with business intelligence tools
  • 1+ years of professional experience with big data technologies like Hadoop, Hive, Spark, H2o and others
  • 1+ years of experience creating prototypes in R, Python, Scala, Java or similar stack to demonstrate the results of algorithmic approaches
  • 2+ years of Agile Software Development experience
  • Advanced degree in quantitative field, computer science, statistics, applied mathematics or similar
169

Senior Data Scientist Resume Examples & Samples

  • TS/SCI Clearance
  • Experience developing and using advanced software programs, algorithms, querying and automated processes to cleanse, integrate and evaluate datasets
  • Possess strong communication, problem-solving, relationship and consensus-building skills and a high degree of personal initiative and attention to detail
170

Senior Data Scientist Resume Examples & Samples

  • Degree in Computer Science, Electrical Engineering, Math, Statistics, Science or related field is preferred
  • Experience in advanced analytics or research and development in machine learning algorithms, statistical modeling is required
  • Strong experience in Java, Scala, Spark, C++ or other programming languages is must
  • Experience using distributed computing systems (Hadoop, HBase) for querying and job runs
  • Familiarity with HTML, Django, JavaScript
171

Senior Data Scientist Resume Examples & Samples

  • Design, develop and program methods and processes to consolidate and analyze sources to generate insights and solutions
  • Specifically, apply data analytics to translate recommendations into business insights
  • Develop and execute statistical and mathematical solutions to business problems within business unit
  • Frame problem then determine intended approach and quantitative methods to develop solution
  • Use analytical and statistical methods to analyze large amounts of data, using advanced statistical techniques such as predictive statistical models, customer profiling, segmentation analysis, survey design and analysis and data mining
  • Develop materials to explain project findings to Management
  • Develop new algorithms and mathematical approaches to understand the company's audiences
  • Solves complex business problems such as optimizing product performance, revenue and adoption
  • Create and deliver presentations
172

Senior Data Scientist Resume Examples & Samples

  • Use analytical rigor and statistical methods to analyze large amounts of data, extracting actionable insights using advanced statistical techniques such as data analysis, data mining, optimization tools, and machine learning techniques and statistics (e.g., predictive models, LTV, propensity models)
  • Develops and executes statistical and mathematical solutions to business problems. Frames problem, develop roadmap, communicates intended approach and quantitative methods to develop solution
  • May serve as a team leader within a work group or on cross-functional teams. Mentors and train junior team members
  • Master's degree, PhD preferred
  • Field of study in Economics, Statistics, Mathematics, Decision Science, Operational Research, Computer Science, Engineering or related field
  • Generally requires 5-8 years related experience
  • Experience with statistical modeling techniques such as regression, decision trees, neural networks, support vector machines, clustering techniques
  • Intermediate to Expert level proficiency with statistical probabilistic modeling techniques such as regression, decision trees, neural networks, support vector machines, clustering techniques, etc
  • Understanding or experience working within an enterprise data warehouse environment, (including SQL, procedural SQL, and ETL) in a relational environments and MPP platforms (Teradata, Netezza, Oracle, etc.)
  • Experience with distributed computing platforms, such as Hadoop, and associated technologies such as MapReduce, Spark, Yarn, and Hive
  • Strong in at least 1 programming language such as Python, Scala, Julia, Java, C++, etc
173

Senior Data Scientist Resume Examples & Samples

  • Serve as the Data Guru of the company - i.e be aware of data streams captured in the company in any format (structured, unstructured, semi-structured, external API etc.)
  • Work on larger programs/initiatives encompassing several projects that have a company-wide impact
  • Assist others in the company in data discovery and data preparation phase
  • Understand the “big picture” our data presents
  • Work closely with various Product, Business and Engineering teams
  • Frame analytic problem statements in response to business and product challenges
  • Be an expert in the Exploratory phase and prescriptive analysis - i.e build and assess models, review results, etc
  • Deployment of various models in Production
  • Articulate storytelling to business & product stakeholders - i.e focus on telling the “business” story that the data shows (and abstract the data complexities and process involved) and have a strong influence on the
  • 2+ years of experience in Data Science and analytics fields
  • Experience in processing and analyzing Big data - i.e large scale data volumes, semi-structured and unstructured data and near real-time throughput
  • Experience working in Hadoop ecosystem
  • Experience building various Machine learning models
  • Strong database knowledge and expertise in SQL
  • Experience using visualization tools such as Tableau and Datameer
  • Good storytelling and presentation skills i.e be able to present business side of the story that data presents to c-team and stakeholders
  • ECommerce domain expertise strongly preferred
  • Masters or Ph.D in Statistics, Math, Computer Science, Market Economics
174

Senior Data Scientist Resume Examples & Samples

  • Direct research, planning, and budget for large and small-scale methodology evaluations and tests
  • Use both qualitative and quantitative methods to improve survey methods and recruitment approaches
  • Manage and analyze complex survey/panel data including developing data files, conducting quality reviews , data editing, documentation, weighting, and imputation
  • Author technical proposals, reports, and articles. Present research to internal stakeholders and at research conferences
  • Master’s degree or PhD in Social or Behavioral/Social Sciences field such as Survey Methodology, Statistics/Sampling, Psychology, Sociology or related field or Bachelors with 3+ years research experience
  • Knowledge of multiple modes of data collection methods, including online and mobile surveys
  • Knowledge of mixed-mode survey designs and panel recruitment and maintenance
  • Creative aptitude and ability and desire to explore opportunities for new research innovations
  • Excellent oral and written communication skills required for presenting to and collaborating with groups of diverse backgrounds
  • Quantitative research and analysis skills including competence with statistical software (SAS or SPSS preferred)
  • Extensive experience with Microsoft Office applications (Word, Excel, Power Point and Project)
175

Senior Data Scientist Resume Examples & Samples

  • Leads and Supports analyses for the Methods group, including product analyses, client inquires, impact of changing methodologies, standards and best practices
  • Leads prototyping (what –ifs) as well as supporting pilot programs for R&D purposes. The primary areas includes – but not limited to – trend analyses, identifying gaps for improvements in coverage, representation/ sampling, bias reduction, indirect estimation, data integration, automation, generalization, harmonization as well as working with different data sources
  • Address major quality escapes
  • Work with cross-functional teams to design, implement, and test new consumer and audience measurement methodologies
  • Assist in the design and testing of data collection methodologies for Nielsen panels and surveys
  • Represents Nielsen within academic and research councils
  • Generate Impact data on proposed methodological changes as to assess impact
  • Support client inquiries including weighing studies and custom analyses relating to methodology
  • B.S. or Masters degree in Statistics, Social Science, Operation Research, or other hard sciences (e.g. Engineering, Computer Science, Biology, Physics etc.) with outstanding analytical expertise or equivalent experience
  • Experience in trend analyses, multivariate statistics (parametric/ non-parametric), sampling, bias reduction, indirect estimation, data aggregation techniques, automation, generalization
  • Proficient in SAS, SPSS, R, Stata or other statistical packages
  • Knowledge in SQL, working with Algorithms, and large-scale databases preferred
  • Demonstrates experience in Nielsen methodologies, data collection, platforms, research processes and operations preferred
  • Domain expert in at least one area: Demography, Sampling, Statistics Modeling, Research Practices, Audience Measurement, Data Integration and/or Digital preferred
  • Experience with data visualization tools (e.g. Tableau, Spotfire, Microstrategy) preferred
  • Experience in big data technologies and machine learning preferred
  • Strong communication/writing skills preferred
  • Experience in high-level programming language (e.g. Python) preferred
  • LI-SB2
176

Senior Data Scientist Resume Examples & Samples

  • Design systems, models and data-science pipelines that predict future social performance
  • Model and predict content consumption and affinities for audience segments
  • Mine the social archives to better understand competitor performance
  • Leverage insights, Multi-Channel Attribution initiatives to provide bottom-up marketing optimization recommendations across the company
  • MS /PHD in computer science, data science, mathematics or a related STEM field
  • Professional background in machine learning or data mining and data science using Python, R or Julia
  • Familiarity with statistical modeling and machine learning tools in Python/R
  • You are experienced with Bayesian probabilistic modeling, time series analysis, graphs, deep learning (convolutional neural networks, RNN’s) and textual models (Doc2Vec)
  • You have deep knowledge of databases both relational SQL and unstructured NoSQL technologies
  • Familiarity with modern machine learning methods for regression, recommendation systems, clustering, classification, support vector machines and optimizations techniques like SGD, metaheuristics
  • Ability to think beyond raw data and to understand the underlying business context and sense business opportunities hidden in data
  • You have data visualization skills in D3, plot.ly and JavaScript
  • Self-motivated and independent with ability to handle multiple competing priorities in a fast-paced environment
  • Proven track record of solving challenging problems in both academia and industry
  • Passion for hands-on, "in-the-trenches" work with real-world big data
  • You have a familiarity with social network schemas and APIs (Twitter, FB, Instagram, YouTube, etc.)
  • You can comfortably communicate complex qualitative analysis in clear and precise manner
  • You enjoy strategy and game theory, risk vs reward assessments and ROI optimizations
  • You possess both creative and critical thinking skills and are able to generate unique and novel solutions to unsolved problems in data science, machine learning and business
  • Are enthusiastic about implementing state-of-the-art algorithms published in academic journals to satisfy real-time business needs
177

Senior Data Scientist Resume Examples & Samples

  • Masters’ degree in Computer Science, Engineering, Science, Mathematics, or a related field
  • 3+ years’ data science experience applying data modeling techniques to solving customer problems
  • 3+ years of experience and fluency in using data modeling tools (e.g. R, Pandas, Scikit learn, Mlib, SPSS or Matlab)
  • 3+ years of experience and fluency in programming or scripting language (e.g. Python, Java)
  • 1 year + experience with Hadoop and NoSQL related technologies such as Map Reduce, Spark, Hive, Pig, HBase, mongoDB, Cassandra
  • PhD in Engineering, Science, Mathematics or other relevant field
  • Strong mathematical/statistical background
  • Understanding of data science trends and passion for keeping current with future state of technologies
  • Previous experience in developing data driven solutions for building systems
  • Results driven with a positive can do attitude
  • Knowledge and experience with open source data frameworks
  • Experience in moving prototypes to production in Hadoop and/or other NoSQL platforms
  • Experience in data visualization and presentation tools (e.g. Tableau, Qlik, Ploty, Highcharts, D3)
  • Proven ability to balance probability and statistical theory and algorithm science with pragmatic problem solving skills, and a track record of developing and applying advanced predictive algorithms and behavior models
178

Senior Data Scientist Resume Examples & Samples

  • Collaborate with a team of other data scientists, data engineers, and business subject matter experts in order to solve complex business problems using machine learning and statistics
  • Recommend which approaches will be effective in various situations and will be able to implement these approaches independently without guidance
  • PhD in Statistics, Computer Science (Machine Learning or data processing focus), or other data rich technical field. A PhD can be substituted with significant industry experience in machine learning and statistics
  • 10+ years of experience in applying machine learning techniques and algorithms
  • 7+ years of experience with standard natural language processing techniques
  • Programming proficiency in a subset of Python, R, Java, and Scala
  • Significant experience analyzing data with SQL
  • Applied statistics understanding
  • Exposure to Amazon Web Services (AWS) and cloud-based systems
  • Exposure to large-scale data analysis systems, such as Hadoop or MPP databases
  • 6+ years’ experience in writing technical documents and reports, such as research papers
  • Experience with data visualization tools and methodologies
179

Senior Data Scientist Resume Examples & Samples

  • Build predictive analytics models with Python to generate actionable insights at the level of individual customers, such as cross-sell opportunities and churn prediction
  • Support the development of personalized customer engagement engine to generate customer insights for various teams, such as field sales, e-commerce and direct-to-customer communication teams
  • Work with Sysco technology team to build the customer data-mart, which is the foundation of data-driven and customer-centric marketing initiatives
  • Identify and derive insights regarding customer behaviors and preferences across various sales and marketing channels to inform customer data-mart
  • Support the launch of customer loyalty program with relevant customer insights to drive the right customer behavior and increase customer loyalty
  • Support the creation of presentation slides for executives, regarding customer insights across various business units, such as FreshPoint, Meat Co, USBL, Guest Supply
  • MBA or Master's Degree of Statistics, Computer Science or other similar advanced degrees from a top tier educational institution
  • 5+ years of experience with top-tier firms in big data analytics, market research, management consulting, or comparable role in corporate setting
  • Personable and likeable – able to connect with a broad spectrum of individuals
  • Quick learner in understanding Sysco culture, organization, and financial constraints and working within them
  • Able to build strong working relationships with internal and external stakeholders, partners, and colleagues
  • Good executive presence
  • Able to ‘read’ an audience and identify both the stated and unstated concerns and considerations
180

Senior Data Scientist Resume Examples & Samples

  • Masters degree in Mathematics, Computer Science, Engineering, Economics, or other quantitative disciplines required; PhD in similar disciplines preferred
  • At least five years experience delivering high quality analytics solutions to complex business problems
  • Ability to independently lead projects in highly dynamic and creative environment
  • Ability to successfully implement analytics projects and generate actionable insights and recommendations
  • Experience in building analytics products for enterprise level solutions
  • Ability to work in a matrix environment, influencing people at varying levels of responsibility
181

Senior Data Scientist Resume Examples & Samples

  • Support analyses for Data Science teams including custom analyses, client inquires, impact of changing methodologies, standards and best practices
  • Works with cross-functional teams to design, implement, and test audience measurement methodologies
  • Learn and become an expert in Local TV Nielsen knowledge, with a focus on weighting and computations and new methodologies
  • Learn and become an expert in how big data flows through Nielsen systems
  • Provide oversight and consultation to Data Scientists and Analysts
  • Respond to client inquiries: Examine analysis specifications for completeness, determine how to execute the analysis with available data, modify specifications as needed, provide an estimated delivery date, deliver analyses on time and accurately with a summary of the key insights
  • Convert existing SAS or C code to Python code and perform quality tests
  • Write custom Python code from scratch
  • Key tasks include – but are not limited to – trend analyses, identifying methodological and process improvements, representation/ sampling, bias reduction, indirect estimation, data integration, automation, generalization, harmonization as well as working with different data sources
  • Pro-actively gather information, as needed, to work independently and with a team
  • Preferred Master’s degree in Statistics, Social Science, Operation Research, Mathematics or Computer Science with outstanding analytical expertise. (Bachelor’s degree with additional experience will also be considered.)
  • 3 to 5 years of experience with one or more of the following: python programming, data manipulation, data integration, modeling, weighting, sampling, survey or market research, trend analyses, survey research, multivariate statistics (parametric/ non-parametric), sampling, standard error estimation, bias reduction, indirect estimation, data aggregation techniques, automation, generalization
  • Must be proficient with Python, including Pandas, Numpy, and SciKit
  • Must be proficient in SQL and large-scale databases
  • Must have ability to manipulate, analyze, interpret large data sources, and tell a story from data through analyses
  • Must have strong communication/writing skills
  • Must have ability to work alone and with a team
  • Must have desire to grow as an expert in Local TV Audience Measurement for a long term career
  • Must be a fast learner
  • Preferred proficiency in Unix and one statistical package, SAS or R
  • Demonstrate interest in Nielsen methodologies, data collection, platforms, research processes and operations
  • Preferred experience with data visualization tools (e.g. Tableau, Spotfire, Microstrategy)
  • Preferred experience in big data technologies and machine learning
182

Senior Data Scientist Resume Examples & Samples

  • Translate business objectives into surveys and analytic approaches and hypotheses, balancing art and science
  • Guide development of large sample consumer surveys, partnering with 3rd party survey vendors
  • Develop/maintain predictive models to improve performance of direct mail and other customer contacts
  • Lead application of advanced analytic techniques such as multi-variate regressions, logistic regressions, and latent class segmentations
  • Develop comprehensive understanding of customer segments and leverage insights to assist in creating plans to increase customer value
  • Review customer data for trends, patterns, and causal analysis to assist in understanding our customers behaviors and attitudes
  • Assist with the design, execution, and analytical support of primary customer research (qualitative and quantitative) to assess customer satisfaction with current programs, products, initiatives and offers
  • Clearly summarize data and analysis in a simple and concise format
183

Senior Data Scientist Resume Examples & Samples

  • Understand the business problem, identify the key challenges, formulate the machine learning problem and provide/prototype solutions
  • Be able to debug and correct your data assumption through AB testing
  • Document the technical details of your work
  • Collaborate and brainstorm with other team members
  • Guide and mentor junior data scientist in best practices regarding methodology (prototype formulation and hypothesis testing), as well as implementation
  • Assess the methodological and functional pros and cons of implementing third-party products versus building an in-house system when facing a business problem
  • Collaborate extensively with stakeholders, program management, and software development team members to ensure that solutions meet business needs, permit valid inferences, and have functional feasibility
  • Passion about solving real world machine learning problem
  • Strong publication record in top machine learning conferences, (ICML, NIPS, KDD, WWW, WSDM, CIKM, ACL and so on)
  • PhD in one of the machine learning related fields: deep learning, graphical modeling, NLP, learning to rank, data mining and web mining
  • Strong programming skills, at least being efficient with one of low level languages, C++/Java, and one of scripting languages Python/R/Scala
  • Experiences with distributed computing (Hadoop/Spark)
  • You must have a minimum of 4 years’ industry experience working with real data (data cleaning, data visualization and modeling)
  • Consumer or ecommerce experience is highly preferred
184

Senior Data Scientist Resume Examples & Samples

  • Responsible for design conception, layout, copy and coordination of production activities to produce high quality graphic artwork
  • Consult and collaborate with department leaders to develop an understanding of communication needs, present ideas and obtain final design approvals
  • Establish art direction for the brand
  • Supervisory experience helpful, but not required
  • Bachelor's degree in Fine or Graphic Arts or related course of study required or equivalent, relevant experience
  • 7 + years of graphic design, marketing and/or advertising experience
  • Strong writing, editing, and creative vision with proven portfolio of projects
  • Good public speaking and presentation skills
  • Interpersonal skills and ability to interact and work with staff at all levels
  • Must be highly artistic, creative with the ability to develop and execute visual ideas that fully support the creative brief
  • Ability to work on multiple projects simultaneously in a deadline driven environment
  • Resourceful self-starter
  • Proofreading and editing
  • Excellent creative writing skills for marketing and advertising
  • Ability to create esthetic designs, determine arrangement of graphic materials, copy, style, and layout on various print mediums
  • Knowledge of graphic design operating systems and imaging software
  • Expertise in Adobe Creative Suite, Photoshop CS, InDesign, Illustrator CS, (Flash a plus but not required)
  • Proficient in Microsoft Office: Outlook, Excel and Word
  • Acrobat Professional including digital workflow via annotations
  • Knowledge of composition, including typography, color and layout
  • Ability to use layers and make masks and use adjustment curves, dcs files and cloning and photo enhancements to create realistic environments
  • Knowledge of printing/publishing requirements and techniques
  • Design and typesetting skills
  • Retouching and color correction experience
  • Pre Press production skills
185

Senior Data Scientist Resume Examples & Samples

  • Develop the tools to best drive insights across the breadth of the Skype Consumer family of products through both aggregate and real time data streams
  • Champion the use of Data Science practices across all aspects of our product and service portfolio and across our business engagements
  • Demonstrate strong communications and presentation skills, and the ability to work across teams to drive results
  • Are a tenacious problem solver that is comfortable with ambiguity
  • Experience with Microsoft Data platforms, COSMOS or ARIA a strong plus, but not required
186

Senior Data Scientist Resume Examples & Samples

  • Conducts advanced data analysis and complex designs algorithm.databases
  • Works with stakeholders to identify the requirements and the expected outcome
  • Works with and alongside analysts by suggesting other products of interest to the consumer
  • Models and frames scenarios that are meaningful and which impact on critical business processes and/or decisions
  • Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes
  • Collaborates with subject matter experts to select the relevant sources of information
  • Works with teams to support data collection, integration, and retention requirements based on the input collected with the business
  • Solves consumer analytics problems and communicates results and methodologies
  • Works in iterative processes with the consumer and validates findings
  • Validates analysis by comparing appropriate samples
  • Employs the appropriate algorithm to discover patterns
  • Works with the data owner to ensure that the information used is in compliance with the regulatory and security policies in place
  • Qualifies where information can be stored or what information, external to the organization, may be used in support of the use case
  • Identifies and analyzes patterns in the volume of data supporting the initiative
  • Demonstrates the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, and fairness
  • Troubleshoots and implements enhancements and fixes to systems as needed
  • Bachelor degree in mathematics, statistics or computer science or related field; Master degree strongly preferred
  • 5-8 years of relevant quantitative and qualitative research and analytics experience
  • Strong programming skills (such as Hadoop MapReduce or other big data frameworks, Java), and statistical modeling (like SAS or R)
  • Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms
  • Knowledge of current technological trends and developments in the area of information security
  • Knowledge of the telecommunication industry
  • Previous leadership experience, a plus
  • Bachelors Degree, Masters preferred, Mathematics, Statistics or Data Science
187

Senior Data Scientist Resume Examples & Samples

  • Tune the algorithms with customer data
  • Scale the algorithms on a big data platforms
  • Integrate with FortiSIEM architecture
  • Experience with machine learning libraries (TensorFlow, Numpy, Matlab, Weka, Mahout etc) and big data platforms (Elastic Search, HDFS, MapReduce, Hive, Mahout)
188

Senior Data Scientist Resume Examples & Samples

  • Masters/PhD in Computer Science, Mathematics, Applied Statistics
  • 3-6 years’ experience working with analytical software (Matlab, Python, SAS, SPSS, R or Weka)
  • Familiarity with Big Data (e.g. Hadoop, Mongo DB, Neo4J, Cassandra, Mahout, Aster )
  • Strong rational ability, communication, inter-personal, and presentation skills
  • Experience in design, develop and deploy state-of-art, data-driven descriptive analysis and predictive models to solve problems
  • Rich experience in data manipulation, good sense in data quality, comfortable in dealing with unstructured data
  • Excellent troubleshooting skills and experience with data analytics and process improvement
  • Proven track record in delivering results, go-to-sell spirit
  • Proved data experience in working with large datasets
  • Great passion in big data and aviation industry
  • Demonstrates the initiative to explore alternate technology and approaches to solving problems
  • Skilled in breaking down problems, documenting problem statements and estimating efforts
  • Demonstrates awareness about competitors and industry trends
  • Has the ability to analyze impact of technology choices
  • Ability to takes ownership of small and medium sized tasks and deliver while mentoring and helping team members
  • Ensures understanding of issues and presents clear rationale. Able to speak to mutual needs and win-win solutions. Uses two-way communication to influence outcomes and ongoing results
  • Identifies misalignments with goals, objectives, and work direction against the organizational strategy. Makes suggestions to course correct
  • Continuously measures deliverables of self and team against scheduled commitments. Effectively balances different, competing objectives
  • Effective team building and problem solving abilities
  • Persists to completion, especially in the face of overwhelming odds and setbacks. Pushes self for results; pushes others for results through team spirit
  • Knowledge of aviation industry is a plus
  • Experience in working with Hadoop/Pig/Datarush, etc. big data processing platform is a plus
189

Senior Data Scientist Resume Examples & Samples

  • Masters degree in Computer Science, Electrical Engineering, Applied Mathematics, Statistics or Physics
  • Experience working with large data stores and distributed computing, and some experience in building software
  • Solid foundation in applied mathematics, such as: statistics, linear algebra, optimization
  • Detail oriented, excellent quantitative, written, and oral communication skills
  • 5+ years experience in software development (Java, Scala etc.)
  • Hands on with Hadoop, Spark technologies
  • Working knowledge about 4G LTE network architecture and SDN (Software Defined Network)
190

Senior Data Scientist Resume Examples & Samples

  • Providing thought leadership in the implementation of engineering solutions
  • Communicating with data scientists and statisticians
  • Identifying opportunities for improvement within existing software applications and frameworks
  • Acting as a source of knowledge and mentorship for non-engineering background data scientists
  • Being agile in a non-agile software development environment: setting your own deadlines and providing project status updates when necessary
  • 2+ years experience in software development with a computer science bachelors degree or 1+ years experience with an advanced degree
  • Experience with big data tools (Spark, Hive, Hadoop, etc.)
  • Fluency with one or more high level programming languages (Python, Scala, Julia)
  • Experience with C or Java
  • Some computer science niche ability: Javascript/D3 web-stack hacker, low level GPU programmer, expert in parallel programming, puppet/packer/docker pro, etc
  • Deep understanding of computer science: Data structures and algorithmic complexity theory are the first things you think of when designing an algorithm
  • Linux pro with no fear of administering your own machines
  • Fan of not inventing the wheel by utilizing and improving open source solutions to complex problems
  • Exceptional problem solving skills with unrelenting focus on business implications
191

Senior Data Scientist Resume Examples & Samples

  • Research new fraud detection techniques
  • Apply classification clustering, data reduction, sampling and evaluation
  • Design and execute data mining analysis for clients
  • Participate in the design, development and maintenance of Analytics engine
192

Senior Data Scientist Resume Examples & Samples

  • Strong statistical data analysis background and a deep understanding of a variety of algorithms and techniques and their applicability to real world problems
  • Experience advancing business using science and data. In depth understanding in at least one of the business areas such as retail, finance, sales, e-commerce, or health care
  • Thorough understanding of experimental practices, error analysis, and evaluation approaches
  • Extensive data cleaning and manipulation experience
  • Comfortable with standard machine learning toolkits, preferably Java- or Python-based
  • Ability to build solution prototypes in a language such as Python, R, or Java
  • Strong communication skills. Experience presenting experimental findings to people who are not Data Scientists or ML experts
  • Ability to collaborate with researchers and translate existing research into practical solutions and products
  • Ability to build and maintain relationships with various collaborators across the company, and take ownership of data science projects and proof of concepts
  • Experience with distributed platforms such as Spark or Hadoop
  • Experience working with large scale database schemas and SQL
  • Experience using Unix
  • Familiarity with data visualization tools
  • Familiarity with ML as it is applied to text processing tasks such as statistical Natural Language Processing and text classification
  • Familiarity with graphical models and deep learning models, including deep learning frameworks such as TensorFlow, Torch, or Theano
193

Senior Data Scientist Resume Examples & Samples

  • Be a leader and mentor to junior members of the team
  • Work closely with Intelligence Analysts to identify and implement workflow improvements and efficiencies
  • Creatively collaborate with users to help them automate simple to complex tasks
  • Develop, test, and deploy analytic solutions, working with end-users to incorporate feedback into the development process
  • Ingest and analyze structured and unstructured data
  • Help users Identify, collect, and organize end user requirements, forming a backlog and ensuring requested specifications and capabilities are accurately described and in sufficient detail
  • Identify, research, and integrate leading edge technologies and tools as required
  • Coordinate with government staff and their customers to validate, prioritize, and track progress of requirements completion
  • Compile reports on performance/usage metrics, schedules, and technology that supports intelligence production roadmaps
  • Participate in technical exchange and senior-level working group meetings
  • Candidate must possess a Bachelor’s degree in Computer Science or related technical field or substantive training and experience in this area, as well as, have at least 7 years of experience in developing software applications
  • Experience leading an Agile team
  • Extensive Java development experience (Django, JSON, Elasticsearch)
  • Experience with agile development methodologies and practices – deskside development, Scrum, user stories, backlogs, continuous integration, retrospectives, etc
  • Experience with HTML, Python, Hadoop, Spark, Julia, Scala, CentOS, API development and JavaScript
  • Excellent interpersonal and communications skills necessary to function within a team environment
  • Security+ certified
  • Experience in intelligence analysis
  • Experience developing analytic applications for an IC organization (on a secured network)
  • Interest in and knowledge of data science tools and techniques
194

Senior Data Scientist Resume Examples & Samples

  • 5 years + hands-on experience in one or more Statistical Methods, such as machine learning, information retrieval, data mining, Text Mining, Natural Language Processing, Web Analytics or similar
  • Experience with Java
  • Experience with SQL and relational database programming and/or distributed computing platforms and query interfaces such as MapReduce, Pig, Hive
  • Excellent verbal and written communication skills; ability to express complex ideas to any level of audience
  • Strong team player capable of working in a demanding environment
  • Eager to learn and apply new technologies
  • Experience working with very large data sets, grouping together data and visualizing results
  • Familiarity with extracting data from Hadoop using frameworks like Hive and from MPP platforms, experience with some Java / python / simple map-reduce jobs development
  • Experience with commercial modelling and simulation tools such as SAS Enterprise Miner, SAS Visual Analytics, IBM SPSS Modeller, and open source tools such as R, Weka
  • Analytical Reasoning Skills: Adept at mathematical reasoning, Applies scientific experimentation to business problems
  • Possess skills such as Analytical Model Design & Implementation, Visualization/Report Design & Implementation
  • Business skills: Some level of industry sector understanding, product understanding and process understanding
  • Strategic Thinking and Creativity Skills: See the Big Picture, have high level of curiosity and willingness to experiment
  • Communication Skills: Excellent Written and Verbal Skills, Ability to communicate effectively with senior level executives clients
195

Senior Data Scientist Resume Examples & Samples

  • Work with the team on demand modeling, forecasting and dynamic pricing
  • Devise techniques for model localization, calibration,monitoring and alerts
  • Be aware of data streams captured in the company in any format (structured, unstructured, semi-structured, external API etc.) and how to overcome their obstacles
  • Understand the “big picture” our data presents and frame analytic problem statements in response to business and product challenges
  • Articulate storytelling to business stakeholders - focus on telling the “business” story (abstracting data complexities and processes)and influencing the audience
  • 8+ years of experience in Data Science and analytics fields with projects from ideation to production
  • Experience working in internet-based/eCommerce/travel industry is preferred
  • Experience with programming languages such as R, Python,or Scala
  • Experience in processing and analyzing large scale data volumes for semi-structured and unstructured data at near real-time throughput
  • Experience working in Hadoop ecosystem, Spark, strong alternative database knowledge and expertise in SQL
  • Experience building various machine learning models and implementation in a production system
  • Revenue management or pricing domain expertise strongly preferred
  • Masters or Ph.D in Decision Systems, Operations Research, Statistics, Math, Computer Science, Market Economics
196

Senior Data Scientist Resume Examples & Samples

  • Leading and coaching less experienced data scientists
  • Perform formal and informal teaching and knowledge sharing, active contribution in communities
  • Defining and leading adoption of new techniques and algorithms from research (internal and external)
  • Lead advanced analytics discovery workshops, ensuring good business understanding, business & analytics success criteria and data requirements
  • Produce analytics assets to be used in go-to-market initiatives
  • Post-graduate degree in related field or extensive professional experience
  • Excellent communication skills; track record of successfully communicating insights to an executive audience
  • Excellent understanding of machine learning techniques and algorithms, such as Support Vector Machine, Neural networks and Decision Tree modelling, ARIMA(x), Random Forests, etc
  • Three years of experience in modelling and analysis with R, Python, SPSS (Statistics and Modeller), SAS, RapidMiner, or comparable product
  • Experience with data visualisation tools, such as D3.js, GGplot, Shiny, matplotlib, etc
  • Experience with Apache Spark, Hadoop, Kafka
  • Some experience of programming in Python, Java, Scala, or R
197

Senior Data Scientist Resume Examples & Samples

  • Building machine learning algorithms
  • Designing visual interfaces
  • Data mining/cleansing
  • Researching analytics software
  • Discovering trends
  • Communicating with executives
  • BS in Computer Science/ Mathematics/ Statistics or equivalent work experience
  • 4+ years of overall experience, 2+ years hands on experience in machine learning
  • Experience in predictive analytics, data mining and machine learning using R and tools like RapidMiner
  • Deep exposure to statistics and analytics
  • Experience in unsupervised learning and segmentation techniques on the consumer data
  • Demonstrated ability to use knowledge of current techniques, and develop new methodologies
  • Demonstrated experience in applying Machine Learning to real-world problems
  • Experience in building and leading high-performing teams, entrepreneurial spirit
  • Experience with Teradata SQL, MS SQL server and Data Visualization using Tableau
  • Proven project work with evidence of creative and critical thinking
  • Superior analytical, problem solving and organizational skills
  • Curiosity about new technology and the possibilities it creates
  • Demonstrated ability to thrive in a dynamic environment and meet deadlines
  • Knowledge of big data tools like Hadoop, Hive and Pig
  • Previous background in web/app development
  • Master’s degree desired
198

Senior Data Scientist Resume Examples & Samples

  • Undertake independent validation and examination of the qualitative aspects of credit risk models for the bank
  • Document validation findings and produce validation reports on the performance of the qualitative aspects of the models
  • Actively participate in development and implementation of methodologies and standards for validation of the bank’s models
  • Ensure that the validation methodologies and standards are in line with industry best practice and that they address regulatory and audit requirements
  • Work closely with the Decision Sciences Model Development team to ensure a transparent and robust model governance structure is in place
  • Serve as a mentor and foster the career development of junior professional staff members
  • Work with DFS Global Credit Services & Decision Sciences teams to develop new processes & procedures
199

Senior Data Scientist Resume Examples & Samples

  • Build a detailed understanding of the problem domain and related data assets
  • Work with technical groups to support the collection, integration and retention of the data sources
  • Research, implement and evaluate machine learning methods and models. Provide ongoing improvement to methods that lead to new information
  • Lead and code the data processing and analytic methods
  • Apply data visualization and summarization techniques to the analytical results
  • Participate in data architecture decisions and technology deployments to support the information processing of large datasets
  • Perform adhoc data exploratory statistical services
  • Graduate Degree (MS, PhD) in Mathematics, Engineering, Computer Science or related field
  • 10 years of related technical experience with 5 years of analytics
  • Knowledge of relational databases and the Hadoop software framework
  • Proficiency with a statistical programming language such as R or SAS
  • Proficiency with C, Java, Python, and SQL programming languages, with knowledge of related data analysis libraries
  • At least 10 years experience with developing and implementing applications
  • At least 7 years experience with the concepts, philosophies and tools behind the design of applications, information and underlying information technologies
  • Extensive knowledge of Probability, Regression, Time Series, and Multivariate Statistics
  • Experience in traditional data processing, data mining, and text mining methods
  • Experience in theory and practice of Machine Learning algorithms to classify and cluster datasets
  • Experience in theory and practice of Natural Language Processing and Entity Resolution for integration and analysis of unstructured datasets
200

Senior Data Scientist Resume Examples & Samples

  • Advocate, evangelize and build data-fueled solutions that help our business teams and customers create joint value. You’ll dig in and become an expert on our consumer, shopper, and retail datasets
  • Responsible for modeling complex Customer Development and Category Management problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques
  • Provide insight into leading analytic practices, design and lead iterative learning and development cycles, and ultimately produce new and creative analytic solutions that will become part of our core deliverables
  • Lead applied analytics initiatives that are leveraged across the breadth of our solutions for our customer development and category management function
  • Ability to clearly propose analytics strategies and solutions that challenge and expand the thinking of everyone around you
  • Master’s Degree or Ph.D. in operations research, applied statistics, data mining, machine learning, physics or a related quantitative discipline
  • 5+ years of experience delivering world-class data science outcomes, with the ability to solve complex analytical problems using quantitative approaches with a blend of analytical, mathematical and technical skills
  • Expert in analyzing large, complex, multi-dimensional datasets with a variety of tools. Comfortable with statistical analysis environments such as R, MATLAB, SPSS or SAS
  • Experience with BI tools such as Tableau and MicroStrategy. Able to work with relational databases as well as Hadoop-based data mining frameworks
  • Familitar with SQL, Python, Java and C/C++
201

Senior Data Scientist Resume Examples & Samples

  • 40% - Lay the groundwork – hypothesize as an individual researcher and in collaboration with other team members on how to solve problems. Perform data preparation activities, such as collecting, cleaning, and organizing
  • Analyze effectiveness of fraud models to constantly improve tools, procedures, and workflows that minimize risk and enhance customer experience
  • Uses best practices to understand the data and develop statistical, machine learning techniques to build models that address business needs
  • Understands the business’ problems to identify the optimal business solution/modeling approach and support your answers and findings with appropriate statistical techniques and methods
  • 30 % - Turn data into insight – segment, cluster, model, and mine to better understand the behavior in question. Explain what has happened or predict what will in an actionable fashion.?
  • Transform data into insights, to identify and quantify opportunities to reduce fraud and false positive into a positive business impact
  • Use and leveraging internal and external Fraud tools as part of our Fraud operations (e.g., R, SAS, Python, SQL, Hadoop)
  • 30% - Drive change – produce clear, understandable visualizations and reports to share with?Senior Management. Partner with product, digital, engineering, marketing and all line of business to design tests and implement your model findings insights
  • Communicates to team members, leadership and stakeholders on findings to ensure models are well understood and incorporated into business processes
  • Participate and drive data modeling and governance best practices
  • 5 years of relevant experience in risk & fraud analytics/operations
  • Master Degree in a quantitative field, such as Data Analytics, Statistics, Mathematics, Computer Science, Finance
  • 5 years of relevant experience in analytics, statistical/quantitative modeling and/or machine Learning tools (R, Python, etc.) and in using various database tools (e.g. Hadoop, SQL) processing large volumes of structured and unstructured data
202

Senior Data Scientist Resume Examples & Samples

  • Develops and implements analytical and/or statistical methodologies for evaluating consumer research, company processes, business problems, and/or ROI of products and services. Establishes parameters of ad hoc analyses by setting appropriate timeline and work quality guidelines
  • Develops timely, innovative, and objective analysis which leads to fact-based solutions for strategic business issues. Assists in the development of the problem definition and hypothesis formulation process as it relates to the specific business environment
  • Maintains a thorough understanding of statistical and advanced analytical techniques, and guides and mentors lower-level analysts. Conducts analyses, formulates insights, and summarizes and synthesizes findings for presentation to management
  • Maintains an understanding of general business trends and requirements for the major area of support (for example: marketing, merchandising, health care, or customer), and understands the link between analysis and business impact. Validates interpretation of business impact of results and communicates to project team and clients
  • Uses SAS, SQL, or other analytical development tools with large data sets to design analyses and measure key metrics. Collects and merges data from multiple sources and works with large, complex datasets. Uses data mining techniques and programming skills to analyze research data and Walgreen databases to identify areas of improvement of current processes, products, services or analytic models
  • Develops recommendations for effective strategies and tactics to drive performance towards established Company goals
  • Provides consulting services related to study design, data analysis, and reporting. Presents insights and findings on major projects to senior management. Effectively communicates the logic of the analytical process
  • Attends industry training and user conferences to further develop software, programming, or analytic skills. Applies new methodologies to analyze business processes and problems. Builds professional network and personal self-study research projects to enhance project opportunities
  • Takes direction from Lead, Head, Resident and Manager positions and works independently to contribute to project delivery
  • Bachelor’s Degree in a quantitative field such as Statistics, Mathematics, Operations Research, Engineering, Economics, or Finance and at least 3 years of experience in advanced analytics
  • Knowledge of analytical software packages such as SAS & SPSS or SQL and relational databases for advanced analytic applications
  • Experience establishing and maintaining relationships with individuals at all levels of the organization, in the business community and with vendors
  • Master’s Degree in a quantitative field such as Statistics, Mathematics, Operations Research, Engineering, Economics, or Finance. Knowledge of general business trends and requirements in support of major business areas such as Marketing, Merchandising, Healthcare, and Operations
  • Knowledge of advanced statistical concepts and data mining techniques such as: logistic and linear regression, CHAID segmentation, survival analysis, Bayesian methods, optimization and time-series forecasting
  • Knowledge of the link between analysis and business impact
  • Experience with project management (for example: planning, organizing, and managing resources to bring about the successful completion of specific project goals and objectives)
  • Experience developing and delivering presentations to various audience levels within an organization
  • Experience collaborating with both internal and external resources to develop strategies that meet department goals within budget and established timelines
  • Experience in creating insights for business partners as an outcome from advanced analytic applications
203

Senior Data Scientist Resume Examples & Samples

  • Working with cross-functional teams to discover and develop actionable, high-impact data analytics need and opportunity statements in a variety of core business areas
  • Developing industry leading solutions including
  • Requirements: will vary depending upon level and will include some or all of the following
  • 11+ Years Professional Experience
  • A flexible analytic approach that allows for producing results at varying levels of precision
  • Strong listening and communications skills, with ability to clearly and concisely explain complex problems and technologies to non-expert and executive audiences
  • Evidence of being able to transfer solutions to business stakeholders for successful adoption and value realization
  • Highly collaborative work style, with ability to provide leadership to a cross-functional team
204

Senior Data Scientist Resume Examples & Samples

  • Management of specific research projects through to conclusion and recommendations. Present model results to internal clients in a clear and concise fashion that maximizes knowledge transfer and hastens bottom line impact of predictive modeling
  • Assist in the implementation of repeatable processes that ensure consistent, quality delivery of modeling and analytics work from the team. This encompasses responsibility for quality control including ensuring appropriate documentation and peer review processes are in place
  • Ability to build strong customer relation by communicating effectively with both customer and claim data science team
  • Work with customer in development of an end state process flow document
  • Develop and deliver against a well-defined implementation Plan
  • Work with a predictive analytics team. Participate in and lead development and training of staff and consultants. Provide direction and assistance on an ongoing basis to ensure group has knowledge and technical experience to execute against stated agenda
  • Partner with business customers as a key analytics point of contact and as a thought leader to identify research and/or business opportunities that Research & Analytics can support
  • Experience & Skills
  • A minimum of 5 years of experience in an analytic research function in Insurance or Financial Services or related field, strong knowledge of processes and data
  • Experience with predictive modeling including knowledge of statistical theory (regression and multivariate statistics) and data mining techniques and their applications in insurance
  • Ability to set priorities and plans to meet business goals and objectives with a skill set that highlights the ability to lead without having formal authority
  • Experience managing in a project-based environment
  • Very strong communication skills. Must be able to present the results of modeling and analytical initiatives to all levels of audience
  • Familiar with statistical tools such as R, Python, SAS; fluent in the Microsoft suite particularly Excel, Word & PowerPoint
205

Senior Data Scientist Resume Examples & Samples

  • Create new predictive models that improve pricing segmentation and underwriting decisions
  • Monitor existing models to provide business insight
  • Advance the predictive power of existing scoring models, ensuring quality, accuracy, and integration with the operation of the business from start to finish
  • Partner with the business to ensure alignment between our models and business objectives. Communicate changes, impacts, and next steps while anticipating intuitive questions
  • Drive unnecessary complexity out of the process flow and create algorithms that can be easily updated in the future
  • Supervise and coordinate work between onshore and offshore team
  • Degree in statistics, actuarial science, economics, or other quantitative analytic field
  • 3+ years of insurance experience
  • Moderate-to-advanced programming skills in SQL and SAS
  • Predictive modeling experience in SAS, EMB, R or other modeling software
  • Creative thinker with strong business customer relationship and project management skills
206

Senior Data Scientist Resume Examples & Samples

  • Identifying internal and external data sources
  • Analyzing data sources for availability and quality
  • Analyzing source systems and provide business solutions
  • Assisting in high level data analysis
  • Identifying areas of opportunity to improve or enhance existing data processes
  • Work closely with Research Modelers, external and internal data suppliers throughout The Hartford in analyzing data sources, being subject matter data expert, defining business requirements, providing data, and assisting in high level data analysis
  • Activities include Operations Research development, ad hoc and project support, line of business product segment support, operational leadership, pseudo production, maintenance, quality measures and documentation
  • Relate the data to the business processes that generates it and the communication skills to disseminate information regarding the availability, quality, and other characteristics of the data to a diverse audience
  • Coordinating with Enterprise Data Warehouse, internal/external data suppliers and service operations
  • Candidates must have the technical skills to transform, manipulate and store data, the analytical skills to relate the data to the business processes that generates it and the communication skills to disseminate information regarding the availability, quality, and other characteristics of the data to a diverse audience
  • Experience accessing and retrieving data from large data sources
  • Experience with data modeling, data warehousing tools and data bases (e.g. SAS, ETL, Informatica, ORACLE, Teradata, SQL Server, R, Python)
  • Ability to analyze source systems and provide business solutions
  • Experience in creating and tuning SQL Queries
  • Experience with Indexes and basic Data Base Design is a plus
  • Self-starter with a willingness to become a data expert and to learn new skills
  • Results oriented with the ability to multi-task and adjust priorities when necessary
  • Knowledge of call center, underwriting, and Digital Analytics
  • Determine business solutions and translate into actionable steps
  • Bachelor degree or equivalent experience in related field required
207

Senior Data Scientist Resume Examples & Samples

  • Scope and build proof-of-concepts / prototypes using data science techniques directly for TR customers
  • Conceive, develop, and test algorithms with tools like R, Python, etc
  • Build external and internal relationships with technology and business leaders, working closely with colleagues to identify and shape ideas into compelling proposals that engage stakeholders
  • Present proof-of-concepts to customers and grow and maintain relationships with key academic groups and start-ups, acting as an ambassador for TR Labs
  • Work with external and internal partners to identify and deliver Thomson Reuters data and tools needed to build prototypes and proof-of-concepts
  • Locate, clean and wrangle data. Integrate internal and external data sources using API’s
  • 5+ years industry experience in text mining, big data, or machine learning (extensive experience gained through academic research may meet this requirement)
  • Experience producing and rapidly delivering minimum viable products. Building API’s or web-based prototypes
  • Experience working with programming and scripting languages (e.g., Python, R, Scikit-Learn, NumPy, Pandas)
  • Experience with API’s and databases (Relational, NoSQL, Graph databases)
  • Ability to track down complex data integration issues, evaluate different algorithmic approaches, and analyze data to solve problems
  • Willingness to work with structured and unstructured data deriving valuable new insights and possibilities
  • Data Visualization
  • Big data analytics (e.g., Spark, MLlib, Hadoop, Hive, Impala, Solr)
  • Experience in one or more Thomson Reuters verticals (Finance, Risk, Legal, Tax and Accounting)
208

Senior Data Scientist Resume Examples & Samples

  • Graduate and likely postgraduate research degree in a scientific discipline possibly accompanied by business education
  • Knowledge of the Retail Industry. Ideal background would include relevant and recent experience working for a leading retailer, Retail Applications vendor or consulting services organization
  • Sound knowledge and experience in one or more of
  • 3+ years of proven success in a ‘sales’ environment, guiding and persuading others to follow your ideas
  • 3+ years’ experience in data analysis, exploration, preparation, mining, utilizing standard tools such as SQL, R, Python, SAS, SPSS
  • High level presentation skills
  • Experience with Data visualization and visual story-telling
  • Ability to translate complex mathematical, scientific, statistical or other technical concepts into simple terms, understandable to his/her team members
209

Senior Data Scientist Resume Examples & Samples

  • Active Data Warehousing
  • Integrated Big Data Analytics
  • Consult to understand customer business use cases and be able to translate them to use case specifications and vision on how to implement an analytic solution
  • Lead Teradata Analytic Consulting engagements and mentor junior team members during the projects
  • Achieve defined project goals within customer deadlines; proactively communicate status and escalate issues as needed
  • Acts as an industry spokesperson and subject matter expert articulating the value of Teradata’s Analytic ISV Partnerships (SAS, Revolution R, Fuzzy Logix, Hadoop partners) and Teradata Aster value to external audiences
  • Develop new ideas for Teradata Analytic Solutions and Services to take to market. Capture and share IP and experience from client engagements
  • Leverage knowledge in analytic and statistical algorithms to help customer explore methods to improve their business by optimizing the Analytic process and developing new capabilities
  • Perform qualification of prospects to define sales strategies based on a thorough understanding of each prospect’s analytic challenges and business needs
  • Develop demonstrations, presentations, white papers, benchmarking tools and other tools as needed to support sales and marketing
  • Work with marketing on related events in assigned territories such as trade shows and webinars
  • Advise clients and Sales on the use of Big Data solutions and Analytics on non-traditional Data Types (Clickstream, Sensor Data, Machine Data, Unstructured)
  • Professional qualifications in disciplines such as Six Sigma, Business Process Modeling, DevOps and Agile considered a plus
  • 5+ years’ experience in data analysis, exploration, preparation, mining, utilizing standard tools such as R, Python, SAS, SPSS, S+, Teradata Warehouse Miner, Matlab
  • 5+ years’ experience in scripting / program languages (Perl, C, Java) for data manipulation and analysis
  • Experience with MapReduce and Spark frameworks, Hadoop and other distributed/parallel processing systems
  • Demonstrated skills in discovery, validating hypotheses, cross industry knowledge, trend discovery and implementation of analytic programs, both from a hands on development, and a communication of those experiences
210

Senior Data Scientist Resume Examples & Samples

  • Demonstrate a keen interest in, and good understanding of, the “Big Data” technology marketplace and the business trends that are driving the adoption and deployment of relevant technologies
  • Have 5+ years hands-on experience in the design, development or support of analytic solutions based on parallel RDBMS and/ or Hadoop technologies and gained in a pre- or post-sales environment at a leading technology vendor or in an end-user computing organization
  • Be expert consultant who can demonstrate the ability to lead client workshops and to challenge and inspire customers and prospects
  • Represent lead for Big Data analytic matters in project teams
  • Be proficient in the use of SQL and R and be familiar with one of the following programming languages: Java, Python, Scala
  • Possess good analytical and problem-solving skills
  • Be proficient in the use of both written and spoken business German and English
  • Be committed to life-long learning and personal development
211

Senior Data Scientist Resume Examples & Samples

  • Understand customer business use cases and translate them to analytical data models with a vision on how to implement it analytic solutions
  • Clearly communicate the business and technical benefits of analytic solutions to both business and technical audiences
  • Leverage knowledge in analytics, machine learning and statistical analysis to help customers explore methods in analyzing data to make better business decisions
  • Work closely with onshore professional services team to come up with analytic solutions for customers
  • Work closely with other members of the team to implementation of these solutions
  • Experienced in statistical modeling, deep learning, machine learning, natural language processing
  • Ability to write complex SQL
  • Exposure to Spark MLlib and/or Tensorflow is preferred
212

Senior Data Scientist Resume Examples & Samples

  • Building statistical models with tools such as R, Weka, MATLAB, SAS, etc
  • Exploring, manipulating, and visualizing data in big data to find new patterns and signals
  • Familiarity with high dimensionality data, dimensionality reduction, or feature extraction
  • Ideal Senior Data Scientist candidates have this additional experience
  • Specialized areas of data science such as natural language processing, anomaly detection, or model parallelization
  • Professional consulting
  • Do you have what it takes to be a Big Thinker? Apply today to join the best in the industry!
213

Senior Data Scientist Resume Examples & Samples

  • Collaborate with data scientists, product managers and customers and experiment with data analysis techniques to identify quantitative solutions to influence revenue-related decision making
  • Analyze data from diverse data sources and build data solutions to deliver insights to business users to optimize every customer touchpoint
  • Work with software engineers to transform your solutions into enterprise-grade scalable data products
  • Work with customers to see your solutions come to life and drive real-world business value
  • Master’s degree in Computer Science, Computer Engineering, Mathematics and, or Statistics; PhD is a plus
  • Professional experience developing predictive analyses using methods including: Bayesian modeling, multivariate and logistic regression, support vector machines, cluster analysis, decision and regression trees, random forest, neural networks and ensemble methods
  • Experience with distributed machine learning and computing frameworks (Spark, Mahout or equivalent). Applied experience preferred
  • Experience manipulating large datasets and using databases (SQL / NoSQL)
  • Strong programming skill (Python, R, Scala and Java, C++)
  • 5+ years hands-on working experience analyzing data, identifying trends, building awesome data visualizations and implementing end-to-end data pipeline from data preparation, feature engineering, model building, performance evaluation and testing with large datasets
  • Domain knowledge customer relationship management and enterprise sales process is desired
  • Undergraduate or graduate studies in business administration is a plus
  • Experience with agent-based modeling systems a plus
214

Senior Data Scientist Resume Examples & Samples

  • Utilize big data stacks to build scalable pipeline and models
  • As part of DataSpark product team, contribute to the end to end data architecture, leading to the deployment of machine learning capabilities into DataSpark products
  • Write and publish patents, case studies, white papers and research papers as determined by business needs
  • Lead team of researchers/analysts for research topics
  • Prepare research proposal, manage external collaborations
  • 7+ years experience of successful application of machine learning, data mining, and statistical analysis with demonstrable impact and proven tracks records
  • A passion for empirical research, data mining and ad-hoc analysis, and for answering hard questions and identifying new opportunities
  • Familiar with basic software development skills (agile methodologies, testing, version control, …)
215

Senior Data Scientist Resume Examples & Samples

  • Experience with online business
  • Proficiency in Java
  • LI-DB2
216

Senior Data Scientist Resume Examples & Samples

  • Drive the roadmap proactively by identifying opportunities in the data
  • Evaluate and solve business problems rather than focusing on metrics alone
  • Create scalable search applications focused on semantic analysis
  • Identify concrete analytical tasks
  • Develop strategies to extract, resolve, and unify information of various types from numerous disparate data sources
  • Organize and mine massive data sets of both structured and unstructured data
  • Provide thought-leadership in the area of analytics/data science
  • ---------------------------------------------
217

Senior Data Scientist Resume Examples & Samples

  • 10+ years of analytic experience
  • Experience using SAS, Rand Python to manipulate large datasets and develop statistical models
  • Knowledge of Hadoopenvironment and ability to interact with large datasets using tools like HIVE or Pig preferred
  • Proficiency in all areas of advanced mathematical methods for developing predictive models including statistical analyses and machine learning
  • Experience engaging consumers to promote positive behavior change
218

Senior Data Scientist Resume Examples & Samples

  • 5+ years of data analytics experience with Health Care Data that is progressively complex related experience
  • Demonstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and in-depth specialization in some areas
  • 5+ years of Open Source Technology experience
  • Experience with Rational Databases; Able to code and data queries
  • Use strong programming skills to explore, examine and interpret large volumes of data in various forms
  • Anticipates and prevents problems and roadblocks before they occur
219

Senior Data Scientist Resume Examples & Samples

  • Research and develop methods for measuring and analyzing marketing spend effectiveness
  • Research new ways for modeling customer behavior
  • Collaborate with cross-functional stakeholders to understand their business needs
  • Formulate a roadmap of project activity that leads to measurable improvement in business performance metrics/key performance indicators over time
  • Conduct end-to-end analysis that includes data gathering and requirements specification, analysis, ongoing scaled deliverables and presentations
  • Architect, develop and automate analytics solutions
  • Make business recommendations (cost-benefit, invest-divest, forecasting, impact analysis) with effective presentations of findings at multiple levels of stakeholders through displays of quantitative information
  • Develop comprehensive understanding of Tailored Brands data structures and metrics, advocating for changes where needed for both products and sales activity
  • Creatively explore how to use data to continually add value and translate ad hoc questions into flexible methodologies that scale to answer broad problems across the organization
  • MS or PhD in Statistics or related (e.g., Mathematics, Physics, Ops Research)
  • Relevant work experience including statistical software (R, S-Plus, SAS, or similar), databases and scripting languages (such as Python)
  • Demonstrated willingness to both teach others and learn new techniques
  • Experience articulating business questions, pulling from datasets and using statistics to arrive at an answer. Experience translating analysis results into business recommendations
  • Deep interest and aptitude in data, metrics, analysis and trends, and applied knowledge of measurement, statistics and program evaluation
  • Demonstrated problem solving skills and impeccable business judgment. Effective written and verbal communication skills
220

Senior Data Scientist Resume Examples & Samples

  • Lead the continued enhancement of the Company’s revenue management system, interfacing with both internal and external analytical and development resources. This will include direct interaction with a renowned academic expert in the Revenue Management discipline, with whom CubeSmart maintains a consulting relationship
  • In conjunction with another Senior Data Scientist on the team, own the development of demand forecasting and optimization models
  • Assist in the definition, implementation, and refinement of all downstream business applications of any forecasting output, including primary application in the Company’s proprietary revenue management system
  • Design, implement, and evaluate statistical testing protocol for website, call center, and pricing optimization
  • Present business/demand trend information to the senior management team to inform strategic decision making
  • Engage with internal stakeholders, external marketing agencies, consultants, and IT resources to facilitate the collection and interpretation of operational data
  • MS/PhD in a quantitative discipline (Operations Research, Statistics, Engineering, Mathematics) with 1-5 years of relevant professional experience (including relevant internship/externship experience)
  • Strong background in applied statistics (regression analysis), microeconomics (discrete choice modeling) and mathematical optimization
  • Proficient technical programmer (e.g., SQL, MatLab, R, SAS, Excel/VBA, C++, Python, etc.) and statistical analysis experience working with large datasets
  • Some exposure to revenue management and dynamic pricing is a plus
  • Ability to work independently and interface effectively with both technical and non-technical colleagues
  • Strong communication skills are essential
221

Senior Data Scientist Resume Examples & Samples

  • Provide thought leadership on challenging data science problems that aim to make Groupon's marketplace more efficient. Example challenges include: Closing the right merchants, ensuring merchant success, predicting customer CLTV, predicting merchant performance, developing ensemble models, etc
  • Flood the room with elegant data science solutions to business problems and best practices in machine learning
  • Work closely with product and engineering teams to form good hypotheses on how to improve the business. Design, execute and measure experiments to test these hypotheses
  • Interpret and communicate insights and findings from analyses and experiments to product, service, and business managers
222

Senior Data Scientist Resume Examples & Samples

  • Synthesize and leverage big data sets to enhance learnings that inform and advance current research methodologies with implications for our Ad Sales, Integrated Marketing, and Pricing & Inventory teams
  • Utilize cross-platform viewership data (linear television, digital, and social) to create thoughtful and innovative audience analyses in order to solve challenges and support key research initiatives
  • Generate strong storytelling research pieces that position Viacom as the premier media partner for advertisers
  • Apply predictive analytics to selling estimates in order to maximize revenue and minimize liability
  • Conduct analyses and data modeling to uncover trends in consumer and media behaviors and attitudes
  • Elevate the utility of current media research data sources
  • Parlay knowledge and learnings to broader Marketing and Partner Insights team to improve traditional media research methodologies and inspire the adoption of advanced analytics and data science across the organization
  • Enforce Viacom’s position as the leader in data analytics in the media landscape
  • Ability to solve problems strategically and think creatively
  • Strong oral and written communication skills; ability to communicate data in a clear and effective manner
  • Highly organized, strong attention to detail, ability to work under pressure and multitask
  • Knowledge of the media industry and multi-platform media measurement a plus
223

Senior Data Scientist Resume Examples & Samples

  • You will work on research and development projects in the specialist field of medical image processing, focusing in particular on machine learning (e.g. deep learning), pattern recognition, 2D/3D/4D segmentation, modeling and tracking
  • You will lead clearly defined subprojects as part of larger research and development projects
  • You will be responsible for producing prototypes, feasibility studies and specifications, and for implementing product components
  • Your tasks will also include preparing applications for funding, drawing up invention disclosures, and publishing articles in high-ranking specialist magazines as well as giving presentations at conferences
  • You will be responsible for implementing the technology in commercial, scientific and industrial applications
  • You will work in a strategic development project in close collaboration with the business areas of Siemens Healthineers, research groups at our Technology Center in Princeton (USA) and with clinical cooperation partners
  • Your tasks will include identifying and evaluating new technical and medical trends
  • You have successfully completed a doctorate in biomedical engineering, information technology, electrical engineering, physics or another equivalent discipline
  • You have an in-depth theoretical and practical background in machine learning or artificial intelligence with a focus on image analytics and interpretation
  • You have already accumulated several years' professional experience (including your doctorate) in these fields and have established a successful track record, ideally in key roles
  • You have been responsible for several publications in high-ranking specialist magazines and have given presentations at conferences in the fields specified above
  • You have sound programming experience in the C++ and Python programming languages under Windows and Linux as well as practical experience of software tools such as TensorFlow and ITK
  • You possess outstanding written and spoken communication skills in both German and English
  • On a personal level, you are a highly proactive, innovative and analytical team player with a customer-focused, results-oriented and quality-oriented approach
224

Senior Data Scientist Resume Examples & Samples

  • 3+ years of hands-of experience in the Analytics ecosystem
  • Strong expertise in statistics and machine learning
  • Strong SQL knowledge
  • Confidence in the use of analytical tools, e.g.: R, Python, Spark, MapReduce, Hadoop, etc
  • Knowledge of big data analytical techniques and their practical application in order to discover new insights
  • Data manipulation experience to optimize data
  • Ability to travel to client sites as required
225

Senior Data Scientist Resume Examples & Samples

  • Lead data science team and stakeholders to address business challenges by harnessing structured, semi-structured, and unstructured data in a distributed processing environment
  • Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse data sources to generate actionable insights and solutions for client services and product enhancement
  • Design, implement, and maintain statistical models representing transportation network behavior and other transportation related processes
  • Research, interpret, and identify use cases for applying data science techniques against public transportation data
  • Prepare and deliver presentations that effectively describe complex quantitative methods in clear and concise communications
  • Apply an understanding of global and/or local trends and events (e.g., economics, social issues) to assist with the formulation of hypotheses and interpretation of data
  • Keep up to date with technical as well as industry developments, analytics software/tools, trends, and recognized best practices
  • Work within project constraints – funding, resources, schedule, priority, goals
226

Senior Data Scientist Resume Examples & Samples

  • 5+ years of health research, customer engagement/analytics experience
  • Well-versed in statistical model building and concepts
  • Expert level SQL skills
  • Experience using R or Python to manipulate large datasets and develop statistical models
  • Knowledge of data management in a Hadoop environment, including use of Hive
227

Senior Data Scientist Resume Examples & Samples

  • Design, develop and deploy state-of-the-art, data-driven predictive/descriptive models to solve business problems using the latest and most appropriate technologies in statistical modeling and machine learning
  • Create new insights from predictive statistical modeling activities that target and deliver value to our clients
  • Manage, architect and analyze big data in order to build data driven business insights and high impact data models to generate significant business value
  • Create models and processes to collect, distill and interpret data with a view to aid better, more informed decision making
  • Examine and explore data from multiple disparate sources with the goal of discovering insights which in turn can provide competitive advantage for our clients
  • Minimum 5 years' of Data Science experience for Ph.D. candidates and 7 years for Masters candidates
  • Minimum 5 years' of work experience in relevant domains (F&A, Procurement, Fraud, Infrastructure Analytics, eCommerce, Security, Retail, Supply Chain Health Care, Pharma, Retail) – with hands on experience handling data driven decisions
  • Minimum 5 years of experience in at least one of the following – Supervised and Unsupervised Learning, Classification Models, Cluster Analysis, Neural Networks, Non-parametric Methods, Multivariate Statistics, Reliability Models, Markov Models, Stochastic models, Bayesian Models
  • Minimum of 5 years of experience in various statistical and machine learning models, data mining, unstructured data analytics in corporate or academic research environments
  • Minimum 3 years of programming experience (C, C++, Java, SAS, Python)
  • Ability to think creatively to solve real world business problems
228

Senior Data Scientist Resume Examples & Samples

  • Develop a sound understanding of the WDN business model, data and systems; particular focus will be on developing a solid understanding of the principles of pricing, customer acquisition, customer retention and inventory distribution
  • Create new and provide support for existing analytical processes and meet stakeholders’ service expectations
  • Maintain and enhance existing forecasting, regression and classification models; enhance existing models and develop new ones using machine learning techniques
  • Graduate degree (Master’s or PhD) in a quantitatively oriented subject such as Mathematics, Operations Research, Economics, Engineering etc. required
  • Four to seven years of experience in application of quantitative techniques in industry
  • Experience conceptualizing, building and deploying analytical solutions in a business setting
  • Experience building time series forecasting models, gained in an industry setting, required
  • Familiarity with optimization theory, obtained through graduate coursework required, experience using in industry setting preferred
  • Familiarity with applications of machine learning techniques desired, experience using in industry setting preferred
  • Experience using optimization software required; Xpress-MP (Dash optimization) skills highly desired
  • Experience with Hadoop or Spark data processing stack (Hive, Pig, Spark SQL etc.) desired
  • Experience with UNIX and writing shell scripts desired
229

Senior Data Scientist Resume Examples & Samples

  • Guiding development teams applying cutting-edge research insights in Machine Learning and Natural Language Processing to challenges of SAP’s customers
  • Contributing to the efficiency, effectiveness, and improvement of ICSV data science best practices as a thought leader, as an advisor to the leadership of the Innovation Center Silicon Valley as well as SAP’s Chief Innovation Officer
  • Influence & multiply knowledge and skills across SAP’s product development organization with over 20,000 employees
230

Senior Data Scientist Resume Examples & Samples

  • Performs high level data analysis; develops complex algorithms and computational solutions as necessary to support pricing execution and customer modeling
  • Ensures data quality and reliability and provides feedback to business process owners, leadership, and to the Revenue Management department
  • Serves as project owner driving development of clear specifications, data acquisition and analysis, as well as assuming accountability for the deployment of analytic solutions
  • Observes current systems/processes and interacts with the appropriate personnel. Utilizing a variety of sources, collects and analyzes information to support the modeling and analysis
  • Collaborates with and as part of leadership to identify, define, and solve a variety of problems and support various Revenue Management initiatives. Present and communicates information to all levels of the organization (including technical and non-technical audiences, Senior Leadership and Executive Leadership)
  • Prepares management reports defining the problem; documenting the analysis and recommending courses of action in order to determine the best outcomes
  • Knowledge and understanding in how to identify root causes of problems, create effective practical solution approaches, and implement solutions under the tactical demands of business operations
  • Practical knowledge and demonstrated experience of statistical models and methods
  • Knowledge of large relational databases, and SQL programming
  • Programming experience (preferably in Visual Basic and Python)
  • Problem solving and analytical skills
  • Ability to demonstrate a customer service and customer focused mindset
  • Normal setting for this job is: office setting
231

Senior Data Scientist Resume Examples & Samples

  • 3+ years of Machine Learning programming experience with R, Python, SAS, Scala, Java or similar stack
  • 5+ years of Predictive Analytics experience (inclusive of academic experience)
  • 3+ years of hands on experience in applying core Machine Learning methodologies: Regression, Classification, Clustering, Matrix Factorization, Predictive Analytics, Natural Language processing, Decision trees, Support Vector Machines, Neural Networks/ Deep Learning
  • 1+ years of experience creating prototypes in R, Python, SAS, Scala, Java or similar stack to demonstrate the results of algorithmic approaches
  • 2+ years of professional experience with one or more of the following Machine Learning and Cognitive technologies: IBM Watson, Amazon ML, Google Cloud ML, Azure ML Studio or equivalent product
  • Experience incorporating Machine Learning & Al concepts into solution development in a professional capacity
  • Agile Software Development experience
  • Experience with business intelligence tools
  • Experience managing, mentoring or leading others
232

Senior Data Scientist Resume Examples & Samples

  • Analyze large data sets to extract actionable insights
  • Apply machine learning at scale to predict audience behavior and consumption of digital media
  • Develop tailored algorithms for large scale nonlinear optimization problems
  • Collaborate with a team of data scientists, analysts and software engineers to build exceptional, data-driven products
  • Practice meticulous validation to ensure high data cleanliness
  • Strong programming skills
233

Senior Data Scientist Resume Examples & Samples

  • Two (2) years of experience with R, data mining, machine learning, and statistical models and tools including neural networks, decision trees, random forests, support vector machines, Weka, Scala, Python, and optimization algorithms including genetic algorithms and Tabu Search
  • Two (2) years of programming experience with Python, Ruby, Perl, Shell, C, or Java
  • Solving problems involving Big Data
  • Leveraging Hadoop and similar database strategies including NoSQL and Graph Databases
  • Demonstrated knowledge of data science and predictive modeling
234

Senior Data Scientist Resume Examples & Samples

  • Proposing and executing medium-to-large insights projects, end-to-end (initial concept to final presentation or product deployment)
  • Seeking out opportunities to apply analytics to existing processes and embed them into operations and, where possible, re-using content and tools across national, regional and global clients and projects
  • Providing advice to internal and external stakeholders on the suitable use of algorithms, statistics and related topics to achieve their business objectives
  • Fostering a collaborative team-based approach to tackling our clients’ problems
  • Introducing productivity and quality improvement tools and practices, as well as new approaches on how to do data science
  • Developing leading analytics team skills and knowledge sharing through continuous learning here, regionally and globally
235

Senior Data Scientist Resume Examples & Samples

  • Providing real-time business analytics and visualization for Internal customers
  • Prototype Dashboarding / Visualization
  • Maintenance of existing SPLUNK Infrastructure
  • Development/maintenance of visualizations such as reports, real time dashboards based on customer needs
  • Data source management
  • Stakeholder meetings (requirement definition, development, adjustments, presentations)
  • Query development
  • General database knowledge (RDBMS, columnar databases, general SQL understanding)
  • Linux/Shell knowledge is beneficial
  • Hands on experience with SPLUNK (knowledge or experience with additional visualization tools is plus)
  • Hands on experience with Big Data Technologies (AWS Stack, Hadoop)
  • Experience in scripting (Scala, Python, JavaScript... )
  • Good analytical skills, general understanding of coherences
  • Open minded and with the capability of learning new things
  • English language written/spoken
236

Senior Data Scientist Resume Examples & Samples

  • How can we solve dynamic, stochastic routing problems whose complexity is at or beyond the cutting edge of current theory?
  • How do we most effectively combine routing algorithms with demand forecasting models, rider availability models, and restaurant scheduling models?
  • How can we most effectively and automatically nudge riders to maximise their earnings while providing a delightful service to our customers?
  • How can we dynamically price our service?
237

Senior Data Scientist Resume Examples & Samples

  • Design and implement scalable algorithms and data models that automate our diagnosis and remanufacturing process
  • Design and implement big data workflows using Python, SQL, Hadoop, Spark, Matlab and R
  • Devise visualization, debugging, and simulation tools for validation
  • Work with a cross-functional team of hardware engineers, process engineers, software engineers, QA/Validation, designers, and technicians
238

Senior Data Scientist Resume Examples & Samples

  • Experience manipulating and managing multiple, large datasets
  • 5 or more years of progressively complex experience in data analytics
  • Expertise in SQL or SAS, and Python, Rand big data technologies including Hadoopand/orPig
  • Understanding of health care industry, products, and systems preferred
239

Senior Data Scientist Resume Examples & Samples

  • The Senior Data Science Consultant will be responsible for forming and maintaining strategic relationships within and between business units through proactive engagement, consultation and project leadership in the area of advanced analytics including; advanced analysis, data exploration, data mining, data visualization, reporting, and dash-boarding
  • The incumbent will need to work with groups across the enterprise to ensure that these efforts are successful through expert planning, guidance, advice, and execution
  • With minimal supervision, the Senior Data Science Consultant (2) will
  • Partner with Business Clients
  • Ability to identify, establish professional relationship, and communicate with analytics clients in order to understand business needs
  • Frame Problems with Stakeholders
  • Ability to research and construct problem frames in order to understand the analysis context and scope that will provide timely, useful results
  • Work in Project Teams
  • Ability to participate in multidisciplinary analytics project teams
  • Interview Subject Matter Experts
  • Ability to plan and conduct individual interviews with experts to gain valid information and data needed for analysis
  • Elicit Information from Groups
  • Ability to plan and conduct group elicitation sessions with committees or other working groups to develop and assess alternatives, uncertainties, and value and risk preferences
  • Communicate Results to Decision Makers
  • Ability to explain the results and conclusions of the analytics process in both written and oral presentation formats
  • Deliver value
  • Conduct statistical modeling and experiment design
  • Conduct scalable data research on and off the cloud
  • Design algorithms and create computer models
  • Implement new or enhanced software designed to access and handle data more efficiently
  • Possesses a minimum of 5-9 years of relevant job experience
  • Graduation from a four year college or university with a degree in statistics, physics, mathematics, engineering, computer science, or management of information systems
  • Possesses a working knowledge of statistics, programming and predictive modeling
  • Possesses code writing abilities
  • Previous experience working in data mining or natural language processing
  • Possesses a mastery of statistics, machine learning, algorithms and advanced mathematics
  • Possesses a combination of creative abilities and business knowledge
  • Shows strong knowledge of basic and advanced prediction models
  • Has data mining knowledge that spans a range of disciplines
  • Has strong critical thinking skills and the ability to relate them to the products or services the company is producing
  • Displays exceptional organizational skills and is detail oriented
  • Master’s degree in business analytics or an advanced computer programming field, statistics, physics, mathematics, engineering, computer science, management of information systems, or related fields or an MBA
  • Ability and desire to develop and maintain good working relationships with internal and external customers
  • Optimistic and enthusiastic with a desire to learn and grow
  • Experience with Spark, Spark Streaming and/or Spark SQL
  • Knowledge of Big Data querying tools
240

Senior Data Scientist Resume Examples & Samples

  • Design, execute and deploy data analysis and modeling projects aimed at solving high-impact business problems for both S&P GMI’s customers and internal clients
  • Play a central role in all stages of the data-science project life cycle, including
  • Identification of suitable data-science project opportunities
  • Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements
  • Data analysis/modeling
  • Evaluation/interpretation of results and presentation to business leaders
  • Partnering with software developers to provide specifications for deploying models/algorithms into production systems, when applicable
  • Prepare the exploratory data analyses, proof-of-concept modeling, and business cases necessary to generate stakeholder buy-in and internal support for your data-science projects
  • Proactively communicate the vision and status of your data-science projects, ensuring that accurate expectations are set and met across all levels of stakeholders
  • Bachelor’s Degree in Math, Statistics, Engineering, Computer Science, or related field; or equivalent experience
  • 3-5+ years experience in a data-science or advanced data-analysis role
  • Demonstrated success in leveraging large amounts of data to solve analytical problems
  • Familiarity with data analysis scripting languages, such as Python or R (Python preferred)
  • Knowledge of advanced statistical data analysis and modeling
  • Experience with data mining, machine learning, natural language processing, and data visualization
  • Working knowledge of traditional data storage technologies, e.g. relational databases, SQL, and ETL tools
  • Exposure to “big data” technologies, e.g. Hadoop, Spark, NoSQL data stores
  • Familiarity with conventional software development languages (Scala, JavaScript, C#, Java, etc.) a plus
  • Ability to collaborate effectively with a diverse group of business, operational and technical stakeholders
  • Ability to communicate complex mathematical models and processes in straightforward, non-technical language
241

Senior Data Scientist Resume Examples & Samples

  • PhD or MS degree in Computer Science, Electrical Engineering, Statistics, Physics, Mathematics, Operations Research or equivalent technical field (5+ years post PhD or 8+ years post M.S.)
  • Expertise in any of the common data science toolkits (Scikit-learn, R, CNTK, Weka, RapidMiner, Theano, Caffe, KNIME, SAS)
  • Software development skills in one or more high level languages (C#/C/C++/Java/F#), one or more scripting languages (Python/Perl/R)
  • Microsoft is an equal opportunity employer
242

Senior Data Scientist Resume Examples & Samples

  • 5 + years of experience applying statistical analyses and analytical methodologies on advanced analytics projects, with the ability to demonstrate the development of algorithms and predictive models to solve business issues
  • 2 + years of experience working on cross-functional/divisional projects
  • Experience with current analytical platforms and be able to utilize these fully independently
  • Highly proficient command of the programming languages SQL, SAS, R, Python, Spark
  • Theoretical knowledge and practical experience in statistical and analytical techniques together with the development of predictive models and machine learning algorithms
  • Working knowledge of Heavy Machinery product lines and the types of data available for each
  • Knowledge of the manufacturing processes as well as Marketing and Customer Support processes
  • Ability to communicate complex analytical insights in a manner which is clearly understandable by the business partners
  • Experience with and ability to integrate unstructured data sets
  • Demonstrated external publications in the field of data and analytics
  • Experience with Machine Learning techniques
  • Experience in Big data solutions, such as Hadoop, AWS
243

Senior Data Scientist Resume Examples & Samples

  • Leads complex global technology realization programs/projects utilizing our internal project execution processes, including Gate Reviews, Design Reviews, and Technical Reviews
  • Project lead is the single point of contact for the entire project. Responsible for creating, executing and tracking all the milestones for the entire project. Assigns roles and responsibilities for the project team members
  • Program lead is responsible for setting the strategy for an entire program that can encompass multiple projects. Responsible to assign project leads and technical leads for all program activities. The single point of contact to upper management for all program activities
  • Serve as (or support) Program Managers in the development of detailed project plans and value proposition. Lead globally diverse cross-functional project teams effectively and manage selected projects under the guidelines of our internal stage-gate process
  • Leads the development of strategies for technology roadmaps for specific applications that are linked to and supportive of the overall CRT and business strategies
  • Participates and presents in ideation events (Innovation Summits, Design Bursts, etc.)
  • Serves as Principal Investigator in government proposal preparation and/or project execution
  • Identifies leading external partnerships, outside technologies and best practices to bring to Eaton
  • Serves as a subject matter expert externally and internally. This includes leadership/active participation in external industry and technical groups, mentoring junior level staff and consulting internal business and engineering partners
  • Master’s in Electrical Engineering, Computer Science, Data Science, Mechanical Engineering, Industrial Engineering, Mathematics or Statistics from an accredited institution
  • Minimum 5 years of experience with predictive modeling using machine learning and sensor fusion techniques with application to power systems
  • Software development skills in one or more high level languages (R/C#/C/C++/Java/Python) and rapid prototyping platform (MATLAB/SIMULINK)
  • Must be able to work in the United States without corporate sponsorship now and within the future
  • Domain knowledge in microgrid, smart grid and commercial building energy management is highly desired
  • Experience developing and realizing predictive modeling and machine learning techniques for power consumption and demand prediction, renewable energy resource forecasting, system and component reliability assessment in practical physical systems
  • Ability to prototype machine learning and sensor fusion algorithms and apply them data driven solutions to problems in new domains and strong business acumen and the ability to understand and formulate compelling value propositions, and to understand and drive through value and adoption chains
  • Experience in building production-grade machine learning and sensor fusion based solutions end to end is a plus
  • Experience with big data and cloud platforms Hadoop, Spark, MS Azure and etc. is highly desired
  • Experience in leading projects with multiple stakeholders in matrix organizations and strong program management skills. Ability to apply six sigma methodologies including QFD, design of experiments, and reliability engineering in the course of their work
  • Experience in writing government proposals is also desired; demonstrated success as evidenced by being selected for funding and successful execution of government sponsored projects is preferred
  • PhD in Electrical Engineering, Computer Science, Data Science, Mechanical Engineering, Industrial Engineering, Mathematics or Statistics with research focus on predictive modeling
  • Green belt certification in DFSS or DMAIC is highly desired
244

Senior Data Scientist Resume Examples & Samples

  • Solid foundation of statistical and data science concepts and in-depth knowledge about various modeling techniques (Logistic, Regression, Trees, SVM, PCA)
  • Experience developing and delivering customer performance metrics: customer value and loyalty modeling with techniques such as segmentation cluster analysis, churn, attrition and propensity models and lifetime value assessments
  • Experience working in a data environment that is large and complex, typically referred to as Big Data
  • Preferred familiarity with either individual/end consumer or enterprise/business segmentation schemas (ideally, both types of schemas)
  • Experience in working to synthesize analytics results with market research for robust segmentation development
  • Interface regularly with senior team leaders and relevant stakeholders across the Adobe organization
  • Contribute to development and adoption of a “customer-centric” mindset across Adobe through analytical frameworks such as corporate and business unit customer segmentation – across individual, small business, and enterprise sectors
  • Identify growth opportunities for the business through the use of various analytical tools and techniques
  • Translate organizational goals and objectives to team and individual projects and deliverables
  • Support Global Marketing Organization and Business Units through multiple analytical disciplines and in partnership with cross functional teams such as IT
  • Be a domain expert for advanced customer analytics, segmentation, and targeting methodology in support of business unit objectives
245

Senior Data Scientist Resume Examples & Samples

  • Continue to work with the customer, post-implementation, to enable them to deploy the solution as widely as possible
  • Document the analytical use-cases - and the benefits that were realized - and share this expert knowledge with the wider, global Teradata, to enable similar solutions to be deployed more widely, thus driving increased levels of business for the Teradata Corporation
  • Have 5+ years hands-on experience in the exploitation of data and the use of advanced statistical and modelling techniques to understand and improve business performance in at least one major industry vertical
  • Demonstrate a keen interest in, and fair understanding of, big data technology and the business trends that are driving the adoption of this technology
  • Demonstrate excellent organizational and people skills, including the ability to work independently and appropriately prioritise between competing opportunities
  • Demonstrate a solid understanding of either: Statistics; Mathematical Modelling; or Behavioural Economics, preferably to post-graduate level
246

Senior Data Scientist Resume Examples & Samples

  • Develop statistical forecasting models and design experiments to answer targeted questions
  • 4+ years of relevant experience with a proven track record of leveraging analytics and large amounts of data to drive significant business impact
  • Passion for learning and innovating new methodologies in the intersection of applied math/probability/statistics/computer science. Proficient at translating unstructured business problems into an abstract mathematical framework
  • Expertise in predictive analytics/statistical modeling/data mining algorithms. Must have knowledge/experience in some/all of the following: Multivariate regression, logistic regression, support vector machines, bagging, boosting, decision trees, lifetime analysis, common clustering algorithms, optimization, stochastic processes
  • Proficiency in at least one declarative programming language such as SQL or HiveQL; one scripting language such as Python, Ruby or Perl; and one statistical analysis language such as R, SAS or SPSS
247

Senior Data Scientist Resume Examples & Samples

  • Work on larger programs/initiatives encompassing several projects that have a company wide impact
  • Articulate storytelling to business & product stakeholders - i.e focus on telling the “business” story that the data shows (and abstract the data complexities and process involved) and have a strong influence on the audience
  • 5+ years of experience in Data Science and analytics fields with a focus on Sort ranking and/or relevancy
248

Senior Data Scientist Resume Examples & Samples

  • Works independently on complex level data gathering, checking, manipulation, and analysis tasks
  • Participates as team member or may be in charge of leading on research, data mining, predictive modeling, and/or business analytics projects
  • Leads medium to large sized research, data mining, predictive modeling, and/or business analytics project teams
  • Builds or manages advanced level statistical and data mining models
  • Handles and resolves questions and issues referred by junior staff
  • Addresses ad-hoc analysis and other duties as required or assigned
  • 6+ years of experience
  • Highly motivated, results-­oriented, creative and nimble problem solver who uses technical data analytics skills and a willingness to go above and beyond to deliver business value quickly
  • Strong working knowledge of insurance industry
  • Strong working knowledge with statistical modeling tools and simulation software such as SAS/SPSS/R
  • Excellent oral and written communication skills, including the ability to explain complicated quantitative concepts to non-­technical stakeholders
  • Ability to translate business requirements into detailed analysis plans. Ability to prioritize requests to meet the most important and urgent business needs
  • Able to work in a matrix management environment
  • Focuses on customers
  • Master's degree in quantitative discipline (i.e., mathematics, statistics, economics, finance) and at least 2 years of related work experience
249

Senior Data Scientist Resume Examples & Samples

  • Partner with internal stakeholders to guide, advise and provide insights on a wide range of business questions
  • Be a trailblazer in the implementation and deployment of Machine Learning algorithms
  • Oversight and execute on supervised, unsupervised and unstructured supervised methods within the machine learning framework
  • Able to identify and execute against data, tools, methods and insight delivery
  • Deep collaboration with the IM, IT and other members of analytical community to drive unique and innovative machine learning analytics and data science solutions
  • Advanced degree or equivalent and at least 8 years experience in related analytics
  • Demonstrates thought leadership
  • Proactive, creative, innovative and collaborative
  • Applied knowledge of supervised and unsupervised machine learning algorithms
  • Experience with statistical modeling and experimental design
  • Hands on experience in developing, optimizing and operationalizing algorithms into near real-time production environments
  • Experience in programming/scripting languages: Python, Java, Scala
  • Experience in statistical programming: SAS, R
  • Familiarity with database and data store languages and tools necessary for a variety of problems including: SQL, NoSQL, Oracle, Teradata, Hadoop, MapReduce
  • Strong presentation and storytelling skills
  • Experience with BI and / or visualization tools
250

Senior Data Scientist Resume Examples & Samples

  • Work with internal and external technology experts on A.I. (Artificial Intelligence) projects to define scope, design algorithms and validate solutions
  • Evaluate partners, service providers and suppliers in the area of A.I. (Artificial Intelligence)
  • Communicate and speak the language of developers in A.I. (Artificial Intelligence)
  • Read and comment and validate A.I. (Artificial Intelligence) software development reports and validation reports and sign off software releases
  • Design machine learning/data mining algorithms to solve real world problems in drug development or process optimization
  • Develop software system in R or Python or other machine learning languages to implement the algorithms and to deploy the solutions
  • Operate in a fast, dynamic environment focused on AGGRESSIVE growth and work independently and effectively across the global organization
  • Identify issues, orchestrate actions, and direct resolution across a global and cross functional group of colleagues
  • Work in a global matrix organization model and interact effectively and develop consensus with all levels of management/senior management within a multi-functional team environment
  • Adhere to global project management best practices and standards and helps direct the IT community in those practices
  • Bachelor’s degree in a relevant business or technical field with a minimum of ten (10) years experience in applying machine learning/data mining technology to real world problems, Master's degree with eight (8) years experience, or a Ph.D. with six (6) years of experience
  • Detailed knowledge of software development lifecyle, business process management, project management concepts, best practices and related polices
  • Demonstrated ability to work in a global matrix organization model and interact effectively and develop consensus with management within a multi-functional team environment
  • Highly developed communication (oral and written), conflict management, and effective influencing skills are all important, as relationships must be developed and maintained with senior management
  • Innovative, persistent and committed to a successful completion of assignments on-time with complete accuracy
  • Exceptional organizational and interpersonal skills
  • Three (3) plus years of experience in R or Python
  • Five (5) plus years of other machine learning languages (i.e. MATLAB, SAS)
  • Experience with big data analytics (i.e. Hadoop, Sparc) and one of the deep learning tools (i.e. Caffe, Tensorflow, CNTK, MXNet, Theano)