Data Scientist / Data Analytics Resume Samples

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LY
L Yost
Lennie
Yost
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Experience Experience
Philadelphia, PA
Data Scientist, Advanced Analytics
Philadelphia, PA
Johns-Davis
Philadelphia, PA
Data Scientist, Advanced Analytics
  • Provide summary statistics of key performance metrics and other measures deemed significant business units
  • Coordinate and manage data analytics activities with stakeholders
  • Perform multivariate analysis, predictive modelling, cluster, market basket analysis using sophisticated statistical techniques
  • Interpret & translate analytic output into insights
  • Determine the source of the data, coordinate extraction and acquisition
  • Work with brands and business units to ensure that all consumer and behavioral data is stored in a centralized enterprise repository using Amazon Web Services, Redshift and C3
  • Assess data quality, identify gaps in the data and eliminate irrelevant data
Houston, TX
Senior Data Scientist, Advanced Analytics
Houston, TX
Lindgren, Barton and Watsica
Houston, TX
Senior Data Scientist, Advanced Analytics
  • Collaborate with internal stakeholders to develop tools and services such as modeling, dashboard development, decision aids and business case analysis to drive innovation, strategic initiatives and recommend solutions
  • Implement measurement & documentation framework against all project work
  • Create, assess, evaluate & Iteratively improve models
  • Develop & implement models to support Group Functions strategy and business pillar initiatives
  • Peer review other Data scientists work
  • Leverage sound judgment, balancing analysis effort versus incremental improvement
  • Provide thought leadership around analytics methodology, tools, and measurement
present
Boston, MA
Analytics Senior Data Scientist / Architect
Boston, MA
Flatley, Nikolaus and Gibson
present
Boston, MA
Analytics Senior Data Scientist / Architect
present
  • Facilitate design sessions with client, translate functional designs for visual presentation incorporating client feedback
  • Organizes and shapes an engagement team’s strategy to drive success
  • Develops and manages relationships across the whole client base, discussing benefits
  • Drives key meetings and workshops to achieve the outcomes within the deadline
  • Identifying risk/reward opportunities and developing business cases to work with clients in new and different ways to mutual benefits
  • Understands and utilizes the full range of facilitation methods and tools to run effective events
  • Consults and shapes development of the client’s approach to identifying and managing risks and assumptions and for realizing benefits at a department level
Education Education
Bachelor’s Degree in Statistics
Bachelor’s Degree in Statistics
University of North Texas
Bachelor’s Degree in Statistics
Skills Skills
  • Excellent communication, problem solving and analytical skills
  • Ability to lead production of proposals, working across departments, for complex customer solutions
  • Experienced in the development and or integration of BI strategies and solutions that can be used at multiple customer sites to enhance the availability, performance, maintainability and agility of their enterprise
  • Experience with BI Presentations Technology Solutions (Hadoop, Vertica, Business Objects, SAS, other advanced analytic reporting) for medium to large scale deployments
  • Able to lead, coach and mentor others in BI tools and Data Analytic Reporting solutions
  • Develops innovative solutions that can be leveraged for future efficiency as BI solutions evolve
  • Experienced with SDLC processes and methodologies
  • Recognized as a subject matter expert in healthcare (Medicaid/Medicare) and or a subset of the industry such as Payers, Providers or Health Services
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15 Data Scientist / Data Analytics resume templates

1

Data Scientist & Advanced Analytics Resume Examples & Samples

  • Conduct software demonstrations/presentations of the Analytics and Business Intelligence platform that range from standard to custom demonstrations
  • Performing requirements gathering and analysis in order to understand current state processes to ensure that the context and implications of change are understood by the clients and the project team
  • Helping to define ROI, success criteria & acceptance criteria for completion of the solution
  • Evangelize the need and recommend strategies to position advanced analytics in areas such as Predictive/Prescriptive Analytics
  • Work with key partners and software vendors contributing to recommendations on predictive / analytical modeling products, services, protocols, and standards in support of procurement and development efforts
  • Play an advisory role, provide thought leadership & propose advanced analytic solutions to customers
  • Contributing to predictive / analytical modeling standards, reporting, and data analysis methodologies, model management
  • Support proof of concept and pilot scenarios
  • Formulate best-practice methodologies that blend customer requirements with product capabilities
  • 8 + years of work experience in Analytics, Modeling, Reporting or Business Intelligence
  • 5+ years of experience in large and medium projects as a leader in self-directed role
  • Experience in analytic skills with a proven ability to rationalize disparate data sources and the ability to intuit the large picture within a dataset
  • Experience in solving client's analytics problems and effectively communicating results and methodologies
  • Strong understanding and implementation of predictive / analytical modeling techniques, theories, principles, and practices. Specific experience in more than one of: forecast and statistical modeling, machine learning and text mining and sentiment analysis
  • Strong familiarity and experience with data preparation and processing – such as assessment of data quality, new variable creation, variable selection, etc
  • Ability to conduct research into predictive / analytical modeling issues, practices, and products as required. Highly developed customer interaction and presentation skills are mandatory and candidate should be comfortable interacting with Sr. IT and Business Leadership levels
  • Tatistical modeling: Analysis of Variance, Data Transformation, Machine Learning Tools (e.g. pre-processing,
2

Information Analytics Research Data Scientist Resume Examples & Samples

  • Use of advanced statistical methods knowledge to directmulti-analyst teams in the creation, validation, and application of statisticalmodels
  • Manage 2-3 research projects concurrently
  • Demonstrate thorough knowledge of Caterpillar Inc.; itsproducts and services; its internal systems, processes, and procedures; and itsrelevant external influences (competitors, laws and regulations, marketconditions, etc.) to meet or exceed customer expectations
  • Serve as the principal communicator with clients aboutthe status of their project and the solution developed
  • Responsible for meeting customer expectations for theprojects he or she is leading
  • Strong planning and organization skills, excellentinitiative, the ability to delegate tasks effectively, and well-honedinterpersonal and leadership skills
  • Expected to be active in external industry and analyticsprofessional associations, and is encourage to develop his or her analyticreputation through conference presentations or research publications
  • Excellent communicator
  • Applicants must have completedPh.D. desirable (preferably in statistics, economics, mathematics, or a similarfield with quantitative coursework; also consider Marketing Analytics, BusinessAnalytics, Predictive Analytics, Business Intelligence, Business, OperationsResearch, Computational Science and Engineering, Industrial Engineering,Mechanical Engineering, Compute Science, Informatics, Applied Science,Quantitative & Computational Finance, Actuarial Science, or equivalent) and6-8 years of progressively responsible, professional experience utilizingquantitative analytics, or Master’s degree (in similar areas) with 13/15 yearsof professional experience utilizing quantitative analytics
  • Must be highly proficient with astatistics package like SAS, R, SPSS, Minitab, Tableau, etc
  • 6-8 years analytics professional experience
  • Demonstrated knowledge or aptitude of statistical, data mining or visualization tools
  • Strong demonstrated leadership skills (previous team leadership is necessary)
  • Program / project management skills are critical
  • Superior accountability, decision-making, initiative, innovation and judgment
  • Effectively communicate quantitative information
3

Data Scientist, Advanced Analytics Resume Examples & Samples

  • Design and implement customized solutions based on advanced analytics using at least one of the following: SAS, R or Python
  • Build media mix models to mine media consumption across TV sets, digital and mobile apps
  • Design and maintain advanced data visualization dashboards in Tableau
  • 2+ years’ experience in the field of advanced analytics and data mining
  • Bachelor’s or Masters in a quantitative discipline
  • Programming experience working in a cloud environment
  • Strong influence and relationship management skills; comfortable interacting with all management levels; Prior experience in providing strategic analysis and consulting
4

New Grad-research Scientist Data Analytics Resume Examples & Samples

  • Research and develop cutting-edge technologies in large-scale data analytics and machine learning
  • Advance the development and integration of big data infrastructure that is highly scalable, efficient, and extensible
  • Deliver high-impact intellectual property values through research publications and patents
  • Work with team members and cross-functional teams (internal/external) that include representation from Technology, Product, Operations, Market Research, etc
  • Expertise in data analytics, data mining, machine learning, and related fields
  • Expertise in big data infrastructure and large-scale distributed systems
  • Experience in payments or related industry is desired
5

Data Scientist Revenue Product Analytics Resume Examples & Samples

  • 2+ years of work experience involving quantitative data analysis to solve product problems
  • Undergrad or Masters degree in Math, Economics, Statistics, or related quantitative field
  • Expert with writing and interpreting complex SQL queries
  • Expert with statistical software (preferably R)
  • Expert with Excel & PowerPoint
  • Ability to communicate results clearly and effectively to a broad range of stakeholders; ability to build and manage relationships with business partners
  • Pluses
  • You have worked in a fast-paced environment like investment banking or management consulting
  • Experience with creating dashboards in Tableau
  • Experience with Hadoop (Pig, Scalding)
6

Data Scientist for Analytics Team Resume Examples & Samples

  • M.S. or Ph.D. in computer science or other quantitative discipline (e.g., math or statistics)
  • Recognized expert with significant relevant research experience in at least one of the following fields: data mining, machine learning, statistics, or finance
  • Hands on coding knowledge and experience in Java or similar OO programming languages
  • Familiarity with an data mining tools such as R, Matlab, WEKA or SAS
  • Experience with time series analysis
  • Excellent communication skills in Hebrew and English
  • Finance experience or knowledge – a strong advantage
7

Data Scientist / Advanced Analytics SME Resume Examples & Samples

  • Experience with a range of big data Analytics & cloud architectures, including Business use cases
  • Strong academic background in Statistics/Maths/Advanced Modelling or computer Science from a top tier institute
  • Ability to relate a problem boundary to a statistical model and define business insights
  • Should have hands on experience with machine learning models like Gradient Boosting, Collaborative filtering, Bayesian Methods, Random Forest, SVM, Markov Models etc
  • Should be able to translate a business problem into a statistical/logical problem, solve it and explain it with ease to non-technical audience in business terminology/relevance
  • Develop Algorithms and Models using R/ Python application. Competence in Spark-MLLib will be an additional advantage
  • Experience for the overall design and development of Advanced Analytics platform that integrates with a big data solution
  • High level understanding of Hadoop, NoSQL data stores, data modelling and data management,
  • Develop thought leadership in solution designing using predictive modelling concepts, translating novel ideas into patents
  • Total over 5+ years of hands-on experience in data science and machine learning
  • Strong interpersonal communication with good oral and written communication, presentation, and analytical skills
  • Knowledge of Telco experience and Telco use cases around Network and Customer Analytics will be an added advantage
  • The role requires an overall experience of 10+ years of experience
  • BTECH/MTECH/BStat/MStat/PHD in Statistics/Computer Science or related from IITs/ISI or Reputed NITs
  • Experience of 2+ years in Customer Solutions and Client facing solution roles
  • Demonstrated technical consulting experience in defining new solutions with customers
  • At least 2 years of hands-on experience in developing Advanced Analytics solution within distributed, high performance systems
  • Experience of Telco Domain would be an added advantage
  • Ability to work in a TEAM is a must have
  • Collaborative skills with strong sense of ownership and accountability to work in a distributed team
  • Flair for technical consulting – ability to link technology to business and explain in lucid language
  • Ability to quickly learn new concepts/technologies with minimal handholding
  • Takes initiatives and self motivated
  • LI-RK1
8

Data Scientist for Behavioral Trading Analytics Resume Examples & Samples

  • Solid grasp of linear and non-linear optimization routines
  • A good sense of the practical aspects of implementing optimization routines
  • Solid coding skills relevant for large-scale data analysis, ideally python (pandas/scipy), R, Matlab, SQL
  • Understanding and appreciation of financial markets, investment and portfolio management concepts
  • LI-JB2
  • LI-Priority
9

Data Scientist, Marketing & Analytics Resume Examples & Samples

  • Mine data (structured, unstructured, transactional, etc.) to detect patterns, opportunities and insights that drive our personalization strategy
  • Develops segmentation, propensity, and look-a-like modeling of individuals across known, identified and anonymous audiences
  • Create the analytics to leverage known, inferred and appended information about individuals to facilitate the right content, at the right time, across a guest’s planning, shopping, fulfillment and on-property experience
  • Create a comprehensive understanding of consumer behaviors and attributes that drives strategy, improves the customer experience, and generates revenue
  • Define and produce deliverables that identify opportunities to shape consumer experiences and that inform and inspire internal stakeholders and decision makers
  • Experience programming big data with statistical modeling tools such as SAS, SPSS, or R
  • Ability to manipulate unstructured data with tools such as Python and mine to form insights about the business
  • Familiar with visual analytic tools such as Tableau and Cognos
  • Ability to paint a picture through analytics that will enhance and determine business decisions
  • Capable of pulling down structured data for modeling through SQL
  • Excellent analytical skills required including advanced statistical and data mining techniques
  • Previous experience with marketing, media and customer segmentation strategy required
  • Ability to handle multiple projects required and work independently in a deadline oriented environment
  • Desire to work in a fast paced environment required
  • 3-5 years prior hands-on experience in big data
  • Experience programming with statistical modeling tools to fuel and deliver marketing personalization
  • Strong familiarity with manipulating and mining unstructured data to transform business decisions that impact the bottom line
  • Experience leveraging visual analytics to create a seamless and inspirational story that inspire and inform business leaders with the necessary knowledge to drive revenue and customer loyalty
  • Practice with designing experiments to determine the best path forward
10

Advanced Analytics Senior Data Scientist Resume Examples & Samples

  • 2 years determining mathematical approaches to solve problems, sampling plan and gathering/analyzing/portraying data; advanced quantitative data manipulation, specifically the acquisition, processing, storage, retrieval, and analysis of Intelligence, Surveillance, and Reconnaissance (ISR) reports and products
  • 2 years test-driven development, continuous integration and Agile development
  • 3 years working classified intelligence or Intelligence, Surveillance, and Reconnaissance (ISR) datasets
  • 2 years data visualization utilizing for example Tableau, Javascript, and other tools/languages; programming utilizing two of the following: VBA, Python, SQL/MySQL in a Windows desktop operating environment
  • 5 years determining mathematical approaches to solve problems, sampling plan and gathering/analyzing/portraying data; advanced quantitative data manipulation, specifically the acquisition, processing, storage, retrieval, and analysis of Intelligence, Surveillance, and Reconnaissance (ISR) reports and products
  • 2 years designing/building/managing solutions utilizing for example ILOG CPlex, Python, SQL, Arena, SAS, SPSS, R
  • 2 years statistical analysis and deploying the results of the analysis; data collection/survey; data mining/text mining
  • 5 years test-driven development, continuous integration and Agile development
  • Basic Knowledge database design and maintenance,
  • 5 years working classified intelligence or Intelligence, Surveillance, and Reconnaissance (ISR) datasets
  • 5 years data visualization utilizing for example Tableau, Javascript, and other languages; programming
  • Basic Knowledge ETL
  • Basic Knowledge PHP, Oracle, machine learning, natural language processing
11

Advanced Analytics Senior Data Scientist Resume Examples & Samples

  • At least 2 years experience in determining mathematical approaches to solve problems, sampling plan and gathering/analyzing/portraying data
  • At least 2 years experience designing/building/managing solutions utilizing for example ILOG CPlex, Python, Standard Query Language (SQL), Arena, Statistical Analysis System (SAS), Statistical Package Social Sciences (SPSS), R or other vendors
  • At least 2 years experience in statistical analysis and deploying the results of the analysis
  • At least 2 years experience in data collection/survey
  • At least 2 years experience in data mining/text mining
  • At least 2 years of working proficiency in French and ability to provide accurate English to French and French to English translation of oral and written communications
  • At least 5 years experience in determining mathematical approaches to solve problems, sampling plan and gathering/analyzing/portraying data
  • At least 5 years experience in statistical analysis and deploying the results of the analysis
  • At least 5 years experience in data mining/text mining
  • At least 2 years working in the healthcare commodities industry
  • English: Intermediate knowledge
12

Advanced Analytics Senior Data Scientist Resume Examples & Samples

  • At least 2 years of working proficiency in Portuguese and ability to provide accurate English to Portuguese and Portuguese to English translation of oral and written communications
  • At least 2 years of working proficiency in Spanish
  • At least 2 years of experience working in the healthcare commodities industry
13

Advanced Analytics Senior Data Scientist Resume Examples & Samples

  • 2 years experience with data collection/survey
  • 2 years experience with data mining/text mining
  • 2 years experience with database design, use, and management, including MySQL and NoSQL (specifically mongoDB)
  • 2 years experience with Web development capabilities including HTML5, Javascript, PHP, Grails, and node.js with the ability to build new ways to visualize data
  • 2 years experience with Java, Groovy, Javascript
  • 2 years experience working classified intelligence or Intelligence, Surveillance, and Reconnaissance (ISR) datasets
  • 5 years experience determining mathematical approaches to solve problems, sampling plan and gathering/analyzing data; advanced quantitative data manipulation, specifically the acquisition, processing, storage, retrieval, and analysis of Intelligence, Surveillance, and Reconnaissance (ISR) reports and products
  • 2 years designing/managing solutions utilizing for example ILOG CPlex, Python, SQL, Arena, SAS, SPSS, R
  • 2 years experience with statistical analysis and deploying the results
  • 5 years experience with data collection/survey and data mining/text mining
  • 5 years experience with database design, and management, including MySQL and NoSQL (specifically mongoDB)
  • 5 years experience with Web development capabilities including HTML5, Javascript, PHP, Grails, and node.js
  • 5 years experience with Java, Groovy, Javascript and Linux administration
  • 5 years experience with working classified intelligence or Intelligence, Surveillance, and Reconnaissance (ISR) datasets
14

Data Scientist Data Management Specialist Deloitte Analytics Institute Resume Examples & Samples

  • Design technical architecture and develop data flow processes,
  • In charge of data extraction and data cleansing,
  • Ensure data quality and provide data governance recommendations,
  • Set-up and implement Master Data Management approach to provide business application, e.g. Single Customer View…
  • Design Model dimensions, design workflow and cubes
  • Integration between business needs and technology solutions
  • Experience in Data Warehousing, especially in data integration area,
  • Have advanced skills in sql and hands-on leading ETL, DQM/ MDM tools,
  • Be knowledgeable with different data modeling approaches, and able use modeling tools or develop DDL manually,
  • Prefer to have experience in MDX and OLAP technology,
  • Should be familiar with Advanced Analytics & Modeling
  • English and Chinese skills required
  • 2 to 15 years relevant experience
  • Bachelor or master’s degree in computer sciences, informatics, information management
15

Data Scientist Advanced Analytics Modeling Specialist Deloitte Analytics Institute Resume Examples & Samples

  • Explore diverse data sources and learn from different types of data to get insights and estimate future trends,
  • Must be statistics-minded, able to build data models for various purpose (likelihood, propensity, etc.)
  • High level proficiency with statistics tools: SPSS, SAS, R
  • Big data experience with Hadoop is a plus
  • Must have experience in data mining application for different industries and businesses
  • Experience with Natural Language Processing preferred,
  • English and Chinese skills required,
  • Fresh Grads welcome and 5-10 industry experience is a big plus,
16

Data Scientist, Data Driven Analytics Resume Examples & Samples

  • Contributing to the refinement and ramp-up of the DDA technology and (Big) Data analytics stack (which includes e.g., testing new tools, defining processes and blueprints, developing recommendations on how to handle specific data challenges)
  • Developing scalable, cloud-based analytics "as a service" software products that leverage GfK's data landscape for answering important business questions of our clients
  • Driving successful, data-agnostic analytics projects, by
  • Expert statistical modeling skills (e.g., predictive models)
  • Expert knowledge of analytic programming languages (R is required, but knowledge of further languages, such as Python or Julia is a plus)
  • Experience with using cloud-based analytics platforms, such as Microsoft Azure or Amazon Web Services
  • (Expert) skills with regard to developing data products and transforming algorithms into scalable software(Expert) skills with regard to performance optimized programming (e.g. parallelization, code optimization, C++ integration in R)(Expert) data visualization/visual analytics skills, also using standard tools, such as Microsoft Power BI or Tableau
  • (Expert) knowledge of optimization, data integration, data mining, and machine learning algorithms
  • Experience with handling and integrating data from different sources – structured and unstructured, small or big(Expert) skills with regard to working in Big Data environments (e.g. Hadoop, Map/Reduce, Pig, Hive)
  • (Expert) skills with regard to sourcing of open data (e.g. from Web APIs)Solid understanding of Big Data Architectures
  • (Expert) skills with regard to database handling, in particular SQL
  • Ability to think creatively in addressing real-world business problems analytically, while maintaining the balance between "art & science"
  • Ability to translate sophisticated analytical information into understandable recommendations
  • Strong business understanding – ideally with in-depth experience in a certain industry (e.g. Technology, Media, FMCG,…)
  • Proven project management skillsProven communication, presentation and client facing skills
  • Ability to confidently and clearly communicate in an English business environment (required!)
17

Data Scientist Student for Advanced Analytics Resume Examples & Samples

  • First or second year student currently pursuing M.Sc./Ph.D. in an academic field relevant to machine learning or top notch second/third year student currently pursuing B.Sc in Computer science/ Information technology with relevant experience in data-science
  • Academic experience in relevant courses with data mining/machine-learning algorithms and techniques
  • Capacity to work 2.5 days a week in parallel to the studies
  • Highly and self-motivated
  • Excellent communication skills and strong team players
  • Proven experience in Matlab/R/Python or other vector based language
18

Data Scientist, Advanced Analytics Resume Examples & Samples

  • Determine the source of the data, coordinate extraction and acquisition
  • Explore and discover new data sources, and transform raw data extract through profiling, cleaning, mapping and validation with expert resources
  • Assess data quality, identify gaps in the data and eliminate irrelevant data
  • Provide summary statistics of key performance metrics and other measures deemed significant business units
  • Perform multivariate analysis, predictive modelling, cluster, market basket analysis using sophisticated statistical techniques
  • Apply advanced analytics techniques to reveal actionable insights and drive revenue or efficiency campaigns
  • Present and visualize the data with the relevant use of graphs and charts in business intelligence clients (e.g. Qlikview)
  • Coordinate and manage data analytics activities with stakeholders
  • Support ad-hoc requests for data analysis from stakeholders
  • Bachelor’s degree in Statistics, Mathematics, Engineering, Operations Research, Computer Science, Information Technology or related fields. University graduates are encouraged to apply
  • Up to 5 years work experience in related fields is an advantage but not required
  • Knowledge of descriptive statistics, and use of appropriate charts and visuals for effective reporting
  • Knowledge of R, Python, SAS, Stata, Matlab, SPSS or other related statistical packages
  • Knowledge of machine learning/predictive analytics such as time-series forecasting, regression (linear, GLM, etc.), decision trees, random forests, basket analysis, etc
  • Knowledge of evaluating success of predictive models, both for classification (e.g. Percent Correct Classification, confusion matrix, lift, gain, Receiver Operating Characteristic and Area Under the Curve) and continuous (R-squared, average error, mean squared error, median error, average absolute error, median absolute error) models
  • Advanced knowledge of Microsoft Excel features such as pivot tables, pivot charts, filters, and functions
  • Knowledge of Microsoft SQL and other relational databases preferred but not required
19

Data Scientist, Insurance Analytics Resume Examples & Samples

  • Interact with insurance industry professionals to understand their business and propose technical/statistical approaches
  • Carry out independent investigations/research studies and produce reports and visualizations to communicate your results
  • Write libraries and research tools, developing and maintaining a research infrastructure to accelerate future results
  • Automate repetitive analyses and reports
20

Senior Analytics Specialist / Data Scientist Resume Examples & Samples

  • Collaborate with others within the practice to determine analytics needs for projects
  • Collaborate with industry experts to develop and deliver solutions to clients
  • Plan, develop and perform routine analytics procedures to identify unusual trends, patterns and relationships in transactional, attribute-based and unstructured data sets
  • Design data-driven solutions and models to solve client issues
  • Design predictive models to address client issues
  • Work with disparate data sets from multiple client systems to develop comprehensive analytical models
  • Design and build client-facing deliverables within data analysis and data visualization software
  • Bachelor’s degree required, degree in computer science, analytics, information systems, statistics or a related field required; MS strongly preferred
  • 4+ years of experience with applied machine learning, algorithm development and analytics
  • Experience with Python (SciPy, NumPy, SciKit-Learn), R, Visual Basic and/or RapidMiner
  • Interest in and aptitude for data analytics/business intelligence
  • Ability to understand business environments in various industries
  • Proficient verbal and written communication skills
  • Discipline to perform detailed analytics while maintaining a vision of the overall project objectives
  • Ability to prioritize and execute recurring and non-recurring tasks
  • Team-oriented and collaborative work style
  • High attention to detail
  • Experience with some of the following software packages strongly preferred
21

Center of Excellence Data Analytics Director Chief Data Scientist Resume Examples & Samples

  • Lead a bold agenda around the use of structured and unstructured data in new and creative ways
  • Work with multiple, complex data sources on a large scale
  • Utilize big data and machine learning to build predictive, prescriptive, and cognitive models across a wide variety of client engagements
  • Assist in the development and mentorship of a team of data scientists across the firm to move the analytics capabilities forward
  • Collaborate with the Advisory service line and industry leaders to develop new use cases and expand the business in new directions
  • Perform thorough testing and validation of models and support various aspects of the business with data analytics
  • Work closely with our technology partner and development team to design, build, implement and test a wide variety of analytic models to support client and industry solutions
  • Identify new data sources/patterns that add significant lift to predictive modeling capabilities
  • Bachelor’s degree in Information Technology or a background in machine learning, statistics, bioinformatics, signal processing or related field. A MS or PhD is preferred
  • Seven plus years of experience as a data scientist
  • Proven ability to prioritize and drive solution-centric efforts across a geographically distributed team of business and technology professionals
  • Prior experience in leading and managing a team
  • Results driven with sound judgment and pragmatism demonstrated
  • Strong background/experience with ETL, data mining, statistical analysis, data processing with very large amounts of data
  • Strong business acumen and ability to determine the impact of data at a very high level
  • Strong intuition; ability to advocate for, and ability to dig deep into data
  • Ability to move data around, from a database or an API, through a transformation or to a model and into human-readable form (ROC curve, Excel chart, map, d3 visualization, Tableau, etc.)
  • Experience with Python, Java, R, Storm, Julia, SQL, Matlab, Mahout or a Perl one-liner
  • A working knowledge of the Microsoft Azure and Cortana Intelligence stack
  • Ability to take action, experiment and turn losses into wins by moving forward
  • Big, undefined problems and petabytes challenge you
22

Data Scientist, Marketing Analytics Resume Examples & Samples

  • Full stack scientist
  • Masters in computer science or mathematics
  • 3+ years of experiences as a software engineer, data analyst or data scientist
  • Experience with advanced analytics
  • Proficiency in at least one programming language, preferably R or Python
  • Knowledge of SQL
  • Knowledge of data visualization
  • Strong interest in the gaming industry
23

Operations Excellence Data Scientist Process Analytics Resume Examples & Samples

  • A Bachelor of Science degree in Statistics, Mathematics, Engineering (Chemical, Mechanical, Electrical) or related field
  • A minimum of 5 year’s experience in complex scientific and process engineering problem solving related to chemical, petro-chemical, pulp and paper industry utilizing first principle/statistical modeling, multivariate statistics, and model predictive control or Graduate level education in lieu of work experience
  • Subject matter expertise in data architecture, data mining, large-scale scientific modeling, analysis and support
  • Hands-on experience with state of the art statistical tools (e.g., SAS-JMP, R, Minitab), neural network, genetic programing based platforms
  • High proficiency and up to date knowledge in the evolving science of analytics, data science as applied to scientific and process engineering problems
  • High level of knowledge in the commercially available software platform in analytics and hardware infrastructure/architecture for capability build
  • Graduate degree (MS or PHD) in Statistics, Mathematics, Engineering (Chemical, Mechanical, Electrical) or related area
  • A minimum of 3 years Innovation experience in data science, applied statistics
  • Ability to research a diverse array of related topics and condense into position papers
  • Ability to work cooperatively and strategically in a team environment with all levels on a timely and organized basis
  • Ability to think strategically while balancing several complex agendas
24

Data Scientist Client Insights & Analytics Resume Examples & Samples

  • Masters or PhD in a quantitative field (Computer Science, Mathematics, Statistics, Physics, Engineering)
  • Minimum 8-10 years of industry experience in applying machine learning algorithms and analytical techniques
  • Fluency in R programming, especially ETL and Data Mining procedures
  • Hands-on experience working with large data and computationally intensive algorithms
  • Strong team player with good communication and presentation skills
  • Experience with relational databases and big data infrastructures (Hadoop, SPARK, etc.)
  • Experience in Data Visualization using QlikView, Tableau or Spotfire
  • Experience in scripting using Python
  • Experience in text mining and text analytics using R or Python is a plus
  • Experience with linear/quadratic programming optimizers is a plus
25

Data Scientist, Marketing Analytics Resume Examples & Samples

  • Leverage ‘big data’ native to Online Marketing to enhance and extend Marketing insight
  • Explore new data sources via APIs and scraping. Storing and manipulating data in AWS or similar
  • Text Analytics: Understand the effect of text content on performance and build solutions that endorse successful text elements
  • Discover and define your own work – great sense of ownership and pro-actively finding opportunity
  • Set up multi-variate testing to measure the impact of on-going campaigns and new initiatives
  • Built strong relationships with the Marketing team and communicate findings to business and technical audiences across the company
  • Strong working knowledge of SQL
  • Strong working knowledge in at least one of Java, Python and/or R
  • Experienced in Excel
  • Experienced with Omniture/ Google Analytics
  • Critical thinker, problem solver
  • Bachelor’s Degree in a quantitative field
  • Proven track-record of professional experience
  • Experience with big data environments
  • Fun and easy to work with!
26

Senior Data Scientist IT Audit & Data Analytics Resume Examples & Samples

  • Collaborate with business lines and other stakeholders to enhance Internal Audit's and the Bank's data analysis practices
  • Create and apply model and algorithm testing strategies to measure performance on an ongoing basis
  • Prepare detailed documentation to outline data sources, models and algorithms used and developed, as well as results obtained
  • Degree in Statistics, Computer Science or related field
  • Experience with experimental design, statistical analysis, machine learning and predictive modeling
  • Extensive experience with statistical analysis tools like R, Python (including libraries such as NumPy, Pandas, etc) or SAS
  • Experience with anomaly detection algorithms or text analytics would be an asset
  • Experience working with the Hadoop ecosystem (e.g., Hive, Pig, etc)
  • At least 1 year of experience leading a team of analysts
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Senior Data Scientist Assurance Analytics Competence Center Resume Examples & Samples

  • Meeting with a prospective client to understand their business problems
  • Building a project prototype
  • Leading teams and reviewing work packages of junior professionals (quality control)
  • Coaching young motivated team member to reach their potential
  • Analyzing massive data sets
  • Engaging in workshops to gather client information for projects
  • Creatively extracting data from various client systems
  • Preparing dashboards or data visualizations
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Research Scientist Data Analytics Resume Examples & Samples

  • Requirements gathering and development of value-adding use cases for data-driven solutions and applications in tight cooperation with ABB’s business units and end customers
  • Data pre-processing, evaluation and analysis
  • Development of data analytics models such as predictive models for industrial assets, by applying data mining and machine learning techniques. Development of prototypes and proof-of-concept demonstrators
  • Publishing of results, creation of IP and work in committees
29

Data Scientist, Fleet Analytics Resume Examples & Samples

  • Providing peer review of analysis and supporting production implementation
  • Guiding the definition of the problem and its solution, with prototypes where appropriate
  • Identifying opportunities and driving their solution and implementation
30

Data Scientist Advanced Analytics Expert Resume Examples & Samples

  • Provide hands-on Statistical Tool development, data processing, and statistical analysis for the delivery teams and management scientists
  • Responsible for developing forecasting, predictive and optimization models to empower organizations to make informed decisions
  • Manage and manipulate datasets, including: defining variables, performing calculations and summarizations, and creating solutions to address client business solutions
  • Design and develop reusable analytical models and data driven assets in support of our analytical service offerings
  • Functional knowledge of at least one of the following domains: marketing, risk
  • Statistical programming in tools like R, Python, SAS, SPSS, MATLAB,
  • Knowledge of big data platforms as Hadoop, Cassandra, MongoDB, Hive, Spark .
  • Knowledge of different statistical techniques: temporal series, machine learning, clustering .
  • Applying cross industry these capabilities of different business needs: customer intelligence, marketing intelligence, fraud, process optimization, text mining, real time decision engine, internet of things,.
  • Develop innovative thought leadership and contribute to the creation of points of view on re-usable models by industry solution
  • Knowledge of full life cycle development methodologies
  • Mentor and train junior developers and modelers
  • Ability to meet travel requirements, up to 100%
31

Data Scientist Program Development Analytics Resume Examples & Samples

  • Identify, transform, and organize analytical data including gathering data from disparate sources, aggregating data, and ensuring data integrity
  • Ensure best practices in segmentation and model development, including the ability to perform statistical modeling, create segments using data mining tools, and create ad hoc queries and reports
  • Implementation of customer development strategy including technical communication of the scoring of customers or extraction of customer segments for special treatment
  • Provide measurements and metrics including campaign backend analysis, agent/agency productivity, scorecard metrics, and incremental gain over business-as-usual (BAU)
  • A mixed background in a quantitative or technical field and business field
  • Experience working with a variety of large data sets
  • Experience in data-driven decision making
  • Demonstrated success in using analytics to drive marketing campaigns
  • Comfortable and capable of coding in programming language(s)
  • Passionate about solving data science problems
  • Self-starter who is comfortable of leading initiative, taking ownership and working with little supervision
  • Support end-to-end business analysis and modeling in an effort to lengthen and deepen customer relationships through customer development, cross-sell & upsell, and retention programs
32

Data Scientist Big Data & Analytics Resume Examples & Samples

  • Perform Statistical Natural Language Processing to mine unstructured data, using methods such as document clustering, topic analysis, named entity recognition, document classification, and sentiment analysis
  • Master’s degree from an accredited college/university in Computer Science, Statistics, Mathematics, Engineering, Econometrics, or related fields, with five years of relevant experience and strong knowledge in at least one of the following fields: statistics, data mining, machine learning, statistics, operations research, econometrics, natural language processing, and/or information retrieval; PhD preferred
  • Proficiency in analysis packages (e.g. R, SAS, Matlab) and programming languages (e.g. Python, Ruby, Java, Scala)
  • Ability to work with clients to assess needs, provide assistance, and resolve problems, using excellent problem-solving skills and verbal/written communication to non-technical audiences
  • Ability to travel up to 80%
33

Data Scientist, Big Data & Advanced Analytics Resume Examples & Samples

  • Utilize Teradata Aster in combination with other open source analytics/statistical tools to deliver innovative analytic solutions to our customers
  • Coach and mentor junior team members
  • Skilled in Python with experience using scikit-learn, statsmodels, NumPy and SciPy libraries
  • Skilled in R or other statistical tools like SAS, SPSS or STATA
  • Must be intellectually curious
34

Data Scientist, Advanced Analytics Resume Examples & Samples

  • Provide quantitative and business analytic skills to develop and implement solutions to financial regulatory issues
  • Define the key business problems to be solved and formulate mathematical approaches to solve those given problems
  • Form and maintain trusted relationships with clients and be the 'go-to' contact point
  • Apply oral and written communication skills to proposal development, client presentations and deliverable creation
  • Ibm.com/responsibility/corporateservicecorps/
  • At least 2 years experience in semi-supervised learning and ensemble methods, decision trees, neural networks and risk modeling
  • At least 2 years experience in modeling and mining large datasets using technologies such as R, Matlab, SAS and SPSS
  • At least 1 year experience in data analytics and deployment of models and algorithms into a production environment in order to analyze extremely large volumes of structured data
  • At least 2 years experience in applying advanced analytics/machine learning techniques in a consulting environment
  • At least 3 years experience in semi-supervised learning and ensemble methods, decision trees, neural networks and risk modeling
  • At least 4 years experience in modeling and mining large datasets using technologies such as R, Matlab, SAS and SPSS
  • At least 3 years experience in data analytics and deployment of models and algorithms into a production environment in order to analyze extremely large volumes of structured data
  • At least 2 years experience in requirements development and business analysis
  • At least 4 years experience in applying advanced analytics/machine learning techniques in a consulting environment
35

Data Scientist for Finance Advanced Analytics Resume Examples & Samples

  • Improving forecasting skills, making it more reliable, robust and flexibel. The core of financial business advice is to empower our internal board / senior managers to stay a step ahead. To fulfill this task we need to propel our current forecasting abilities forward by identifying key drivers to the development of our financials and bringing soft / unstructured data in play. When we start excelling at the predictive side, we also aim to step into the realm of prescriptive analytics aiming for well-developed decision support
  • Cost efficiency improvement.An important strategic focus remains on keeping our costs in check. A data scientist can aid in making for example our accounts payable, accounts predictable. Also resource allocation could be an area where a data scientist could add significant value
  • Risk and Finance collaboration to reduce risk (costs). The data scientist can help to improve risk models (e.g. prepayment, replication) and help to better detect or predict risks by developing for example advanced network models on how markets/ companies are related or develop early indicators to detect the early stages of a financial crisis or a housing crisis
36

Research Scientist Optimization & Data-analytics Software Resume Examples & Samples

  • Development of optimization methods for industrial assets
  • Development of prototypes and proof-of-concept demonstrators
  • Communication of project results and complex solutions to expert and management audiences
37

Data Scientist Iv-prepaid Analytics Resume Examples & Samples

  • In addition, this role with consult with marketing and pricing managers, media strategists and deployment teams to design actionable in-market tests that provide measurable and informative insights enabling the organization to achieve acquisition, engagement, and retention goals
  • Design test-and-learn experiments for online and offline marketing initiatives. Provide guidance on statistical power and sample size. Determine measurement, data collection and tracking requirements; utilize measurement systems for data capture and reporting and post-campaign analytics and assessment
  • As part of a team which helps supports not only postpaid analytics but also provides focused support to prepaid products and services, you’ll work on a variety of challenging and creative analytical problems: from pricing optimization to distribution analysis and site selection, from offline to online marketing initiatives, from acquisition targeting to extending customer engagement
  • Master's Degree or PhD in Math, Statistics, Data Science or related analytical field coupled with academic background (eg MBA) or experience in marketing
  • Experience and expertise studying prime and subprime customer buying behaviors
  • 5+ years of experience in the analysis of large data sets to develop insights and learnings (data mining and predictive analytics). Strong analytical skills with understanding of statistical techniques. End-to-end experience in the analytical process: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations. You must be able to analyze raw data, draw conclusions, and develop actionable recommendations. Consulting experience is a plus
  • 3+ years of experience reporting and analyzing marketing campaigns, including developing predictive targeting models, as they inform and drive profitable acquisition and retention of customers. Experience applying marketing/media mix or attribution modeling solutions, pricing optimization routines, retail site location analytics, social network analytics is a differentiator
  • Strong, self-directed execution and organization. Able to lead a project team and foster collaboration. This role will be working with marketers, engineers, and product leads in rapid development cycles, and you should be comfortable executing with little oversight
  • 5+ years of experience explaining advanced analytic concepts and analytic vision to diverse audiences ranging from high level executives, to marketing managers and analysts
  • 3+ years of experience with modeling operations including data collection, model development, productionalization, validation, and monitoring
  • 5+ years of hands-on experience with statistical software packages (e.g. SAS, Alteryx, Aster, R, Python, etc) for analytical data management and building predictive models
  • Experience in building simulation and optimization algorithms a plus
  • Skilled with Microsoft Word and Powerpoint. Able to work with project management and knowledge sharing tools like Sharepoint as part of the role. Data visualization skills (e.g. Tableau, Microstrategy, Excel Power BI, Adobe Workbench). 3-5 years hand-on experience using Excel for reporting and data analysis required. Advanced skills preferred
38

Data Scientist / Data Analytics Resume Examples & Samples

  • Understand how to identify data problems and present the correct analytics technique and implement a solution
  • The ability to extract, transform and load ( ETL ) data using a variety of tools such as Informatica, SSIS and Talend
  • Understand analytic techniques such as multivariable regression analysis, decision trees, random forests, Bayesian inference. Proven ability to understand and apply the correct technique for the right problem
  • Visualize data using a variety of tools such as Tableau, OBIEE, Reporting Services, TIBCO SpotFire
  • Understand had to generate complex SQL queries using techniques such as JOINS, MERGE, INTERSECT, CASE and CURSORS
  • Data Visualization tools such as Tableau, OBIEE, C#, JQuery
39

Senior Data Scientist, Predictive Analytics Resume Examples & Samples

  • Expertise or experience in statistics and signal processing
  • Expertise or experience in object-oriented, analytical programming (e.g., R, Python)
  • Comfortable with SQL, ODBC query logic or equivalent
  • Adept with machine learning algorithms
  • 2 + years of Expertise or experience in statistics and signal processing
  • 2 + years of Expertise or experience in object-oriented, analytical programming (e.g., R, Python)
  • 2 + years of Experience with SQL, ODBC query logic or equivalent
  • 2 + years of Experience with machine learning algorithms
40

Data Scientist Student for Advanced Analytics Resume Examples & Samples

  • Exceptional first or second year student currently pursuing a M.Sc./Ph.D. in an academic field relevant to machine learning or signal processing such as computer science, mathematics, statistics, and electrical engineering
  • Strong theoretical knowledge in topics such as data mining, machine learning, signal processing, and statistics
  • Substantial experience in programming and script languages such as Python/R/Matlab
  • Capacity to work at least 2.5 days a week Highly motivated, methodical, innovation-oriented, communicative and a self-starter. Possible job locations: Petah-Tikva/Jerusalem/Kiryat Gat
41

Data Scientist, Marketing Analytics Resume Examples & Samples

  • Masters or upper degree in Computer Science
  • 3+ years of experience as a software engineer, data engineer or data scientist
  • Proficiency in R, Python or Spark
  • Proficiency in SQL or Hive QL
  • Excellent communication and interpersonal
42

People Analytics & Research Data Scientist Resume Examples & Samples

  • Develop machine learning algorithms
  • Gather, manipulate and analyze large datasets
  • Work with key stakeholders with HR to analyze business needs, forming hypotheses and synthesizing conclusions into recommendations
  • Communicate findings and recommendations on critical initiatives and influence leaders to take action on those findings
  • Work with internal and external technology teams to build the infrastructure required to collect data from various sources – within and outside of HR (including external data sources)
  • Minimum 3 years’ experience in a machine learning/NLP role
  • Strong academic background (Ph.D. preferred) in a related field – Computer Science, Engineering, Physics or Mathematics
  • Comprehensive coding experience in Python or R, experience working with relational databases and SQL
  • Expertise in the design and analysis of data structures and algorithms
  • Excellent analytical skills - ability to analyze large datasets, detect and correct errors, interpret and report results to various audiences
  • Deep interest and aptitude in data, metrics, analysis and trends
  • Excellent interpersonal and communication skills, both written and verbal
  • Results-oriented -- ability to handle multiple, time-sensitive projects while focusing on the quality
  • Team player – collaborative and focused on collective objectives and goals
43

Senior Data Scientist / Head of Analytics Resume Examples & Samples

  • Lead the development of Analytics products for manufacturing environment
  • Drive the decisions on right-fit architecture and tool chain from Analytics point of view
  • Define and develop Analytics product strategy, roadmap, requirements, manage backlogs and direct interfacing with overall business and product development
44

Analytics Senior Data Scientist / Architect Resume Examples & Samples

  • Data and Policy Analysis – strong data and analytics experience, experience with utilization of data for statistical and policy analysis for the generation of reporting in support of EOHHS management, program development and policy decisions. Presentation of such materials
  • Facilitate design sessions with client, translate functional designs for visual presentation incorporating client feedback
  • Organizes and shapes an engagement team’s strategy to drive success
  • Develops and manages relationships across the whole client base, discussing benefits
  • Drives key meetings and workshops to achieve the outcomes within the deadline
  • Identifying risk/reward opportunities and developing business cases to work with clients in new and different ways to mutual benefits
  • Understands and utilizes the full range of facilitation methods and tools to run effective events
  • Consults and shapes development of the client’s approach to identifying and managing risks and assumptions and for realizing benefits at a department level
  • Shapes and directs proposals describing the company solution and the associated value proposition
  • The principal consultant who leads facilitated sessions with business and technology representatives in order to design and/or enhance recommended BI solutions
  • Leads cross functional team, including technical management of client staff assigned to implementation team, in the completion of solution requirements, architecture, and / or implementation deliverables
  • Manages solution design, provides consulting advice to customer and DXC team as needed to ensure overall education on solution progress including benefits and risks
  • Sets strategic direction for customers based on DXC best practices
  • Must work onsite in Rhode Island (DXC client site as needed)
  • 10 years of experience working in Business Intelligence, Data Analytics, Data Warehousing solutions and healthcare industry
  • Advanced Educational degree preferred
  • Excellent communication, problem solving and analytical skills
  • Experienced with SDLC processes and methodologies
  • Experienced in the development and or integration of BI strategies and solutions that can be used at multiple customer sites to enhance the availability, performance, maintainability and agility of their enterprise
  • Develops innovative solutions that can be leveraged for future efficiency as BI solutions evolve
  • Recognized as a subject matter expert in healthcare (Medicaid/Medicare) and or a subset of the industry such as Payers, Providers or Health Services
  • Demonstrated ability to translate business needs into enterprise architecture requirements
  • Experience with BI Presentations Technology Solutions (Hadoop, Vertica, Business Objects, SAS, other advanced analytic reporting) for medium to large scale deployments
  • Solid knowledge and experience in understanding DW infrastructure, Oracle, ETL solutions, logical mapping, data modeling and business requirements to create client deliverables
  • Ability to lead production of proposals, working across departments, for complex customer solutions
  • Able to lead, coach and mentor others in BI tools and Data Analytic Reporting solutions
45

Data Scientist, Predictive Analytics Resume Examples & Samples

  • Research on state-of-art statistical analysis techniques to continuously improve Predictive Analytics team’s competence within the analytics industry
  • Create machine-learning based tools or processes for data mining and data analytics
  • Collaborate with IT partners to build big data platforms to enable big data storage, analytics and applications
  • Translate business problems into statistical problems, develop statistical models and/or customized analysis to support business needs
  • Use advanced analytics to assess portfolio performance, identify business opportunities, and drive critical business decisions
  • Design data-driven marketing initiatives to manage customer relationship, drive sales, enhance executions, and increase productivity
  • Document analysis processes and results, summarize data insights, and present key findings to internal as well as external partners
  • Theoretical or professional experience building sophisticated models via regression, segmentation, decision tree, time series, design of experiments and other multivariate analysis
  • Excellent understanding of machine learning techniques and algorithms, such as SVM, Random Forests, Neural Network, etc
  • Experience with common statistical and data science toolkits to extract and manipulate massive data sets, such as SAS, R, Matlab, Python, H2O, etc
  • Experience in using big data tools for analytics, and expertise in Hadoop ecosystem (HDFS, YARN, Spark, HBase, Hive, etc.)
  • Experienced in bank card / credit card, consulting, retail, marketing, loyalty, and/or financial services
  • Excellent verbal and written communication skills and good at developing interpersonal relationships
  • Highly motivated to achieve and collaborative as well as innovative
  • Master Degree in Statistics, Mathematics, Computer Science, Engineering, Information Systems, Economics, Finance, Business or other quantitative field; or equivalent knowledge or experience
  • Minimum 3 - 5 year directly related work experience
  • Work in an analytics field with exposure to advance quantitative analysis and modeling applied to solve business challenges
  • PhD in quantitative fields
  • Prior experience developing advance technical expertise in a market differentiation product
  • Experienced in bank card/credit card business, consulting, retail, marketing, loyalty, and/or financial services
  • Alliance Data offers a competitive salary and a comprehensive selection of benefit options including 401(k)
  • Alliance Data will consider for employment qualified applicants with criminal and credit histories in a manner consistent with all applicable laws
  • Alliance Data is an Equal Employment Opportunity employer
  • Alliance Data participates in E-Verify
46

Data Scientist, Safety Data Analytics Resume Examples & Samples

  • Collaborate across multiple internal functions (stakeholders) such as Automotive Safety Office (ASO), Research & Advanced Engineering, Product Development, Office of General Council, and Government Affairs, to name a few. A key example is the collaboration with ASO-Advanced Rulemaking and Strategy to develop Company policy and positions
  • Proactively engage with business stakeholders to understand their business needs and to ensure that analytical solutions are practical and business driven, and value-added
  • Employ statistical, econometric, data mining, and mathematical techniques to analyze, model, and produce forecasts related to safety and accident data
  • Interface and support discussions with external private and public entities to support business goals. Examples include
  • 3 or more years’ experience in advanced analytics including modeling work in SAS, R, Minitab, Python, and SQL
  • PhD in Statistics, Industrial Engineering, Operations Research, Economics, Mathematics, or related area
  • Five or more years’ experience in advanced analytics, preferably including modeling work in SAS, R, Minitab, Python, and SQL
  • Experience with crash data analytics, crash testing or crash reconstruction
  • Demonstrated communication and presentation skills
47

Senior Data Scientist, Advanced Analytics Resume Examples & Samples

  • Perform needs analysis with business area (understand business problem & generate hypotheses)
  • Explore, generate & source data relevant to the hypothesis(internal, external, 3rd party)
  • Create, assess, evaluate & Iteratively improve models
  • Calculate model impact/ROI
  • Peer review other Data scientists work
  • Leverage sound judgment, balancing analysis effort versus incremental improvement
  • Generate insights in such a way that the businesses can clearly understand the quantifiable value. Enable the business to make clear trade-offs between and among choices, with a reasonable view into the most likely outcomes of each
  • Turn statistical and computational analysis into user-friendly graphs, charts, and animation. Enable those who aren’t professional data analysts to effectively interpret data. Ability to communicate results and educate others through reports and presentations
  • Provide thought leadership around analytics methodology, tools, and measurement
  • Innovate & find creative ways to source & leverage data to support modeling efforts, leveraging structured & unstructured data, and big data technologies
  • Advanced degree in Statistics, Math, Computer Science, Engineering or other related discipline (post-grad preferred)
  • Minimum of 3 years experience, specifically in statistical/data analysis and data mining, predictive modeling, cluster analysis, and optimization
  • Proficient in Python, R, SAS, SQL, Java, VBA
  • Track of record of delivering innovative analytical insights
  • Strong commitment to organizational success and team work
  • Adaptable and open to change with strong collaboration and communication skills
  • Demonstrated data transformation & manipulation experience
  • Experience with analysis of unstructured data desired
48

Data Scientist, Program Analytics Resume Examples & Samples

  • Design experiments, test hypotheses, and build actionable models to optimize TRMS business processes
  • Adept at translating business needs into technical requirements and translating data into actionable insight
  • Work closely with internal stakeholders such as business teams, product managers, engineering teams, and partner teams
  • Masters in quantitative discipline, e.g. Mathematics, Statistics, Economics, Artificial Intelligence, Engineering
  • 3+ years of hands on experience with statistical software tools: SAS, SPSS, Strata, R, Python or Matlab
  • Experience in using databases (e.g. Oracle, Redshift), and data visualization tools (e.g. Tableau, Microstrategy)
  • 3+ years’ experience in business analytics, forecasting or business planning with emphasis on analytical modeling, quantitative reasoning and metrics reporting preferably from an internet environment
  • 3+ years of writing strong SQL queries in a high volume database environment
  • Experience with visualization technologies such as Tableau
49

Data Scientist Data Analytics Team m Resume Examples & Samples

  • Develop a strong knowledge / feeling for the Business and processes that allow you to identify killer Data Use Cases
  • Focus on delivering projects and creating value for Corporate Banking
  • Explore, clean and handle data
  • Build descriptive and predictive analytical models
  • Handle the industrialization phase of our projects
  • Manage data analytics projects from end-to-end (from ideation to implementation / after care)
50

Data Scientist, Marketing Analytics Resume Examples & Samples

  • Must have 1+ years of hands-on analytics experience working on analytical studies from: crafting the methodology, to data mining / predictive modeling using tools like SAS, R, Python, and ultimately delivering final insightful recommendations
  • Experience building predictive models using SAS, R, Python
  • Marketing analytics experience is a plus (response/spend modeling, retention, churn, cross sell, test design)
51

Data Scientist Data Analytics & Visualization Resume Examples & Samples

  • Good understanding of Maths, Statistics and the theoretical foundations of Machine Learning
  • Experience in the implementation of Machine Learning algorithms
  • Experience in Big Data technologies e.g. Spark/Hadoop
  • Proven track record in advanced Data Structures and Algorithms implementation (Python preferred, but Java/C++/Scala will be considered)
  • Ensures that appropriate standards (corporate, industry, national and international) are adhered to
  • As a strong communicator working as part of a global team
  • Develop a good understanding of End to End business processes and the associated technical blocks
  • Working with production support teams to ensure smooth transition of software developed
  • Willingness to take ownership of tasks and the ability to work on their own initiative while being a strong team player
  • Understand the technical environment and look to continually promote increased knowledge in the team
  • Excellent verbal and written communication skills, able to communicate accurately, concisely and with tact and diplomacy when appropriate
  • Be conscientious, reliable and inquisitive with a keen desire to learn, not just gain the knowledge necessary for the job but also the underlying reasons and drivers
  • The ability to work under pressure within agreed timelines and to support multiple tasks in parallel
  • The candidate will be expected to continually look at improving the processes and procedures in the development life cycle and challenge areas that they see inefficient