Director, Data Science Resume Samples

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J Howe

Julie

Howe

2373 Robel Divide

Philadelphia

+1 (555) 427 2071

2373 Robel Divide

Philadelphia

Phone

p +1 (555) 427 2071

Experience Experience

Detroit, MI

Director Data Science

Detroit, MI

Reilly and Sons

Detroit, MI

Director Data Science

Work with client analysts to assess and balance workload and ensure timely delivery of analytic results
Provide and leverage feedback to improve the collaborative environment of the data science team from a communication and technical perspective
Make presentations to CD&S and BLM teams on analysis performed
Leads development of analytical models using statistical, machine learning and data mining models. Defines model development tactics
Develop and manage a data roadmap including monetization strategies such as client-facing analytics and third-party data sharing opportunities
Work with senior management across product, client, and IT divisions, taking a large role in driving that agenda with business units
Provide expertise on mathematical concepts and inspire the adoption of advanced analytics and data science across the breath of the organization

New York, NY

Director, Data Science

New York, NY

Sauer LLC

New York, NY

Director, Data Science

Work collaboratively with senior management to develop strategy and approach to defining business challenges to be answered by data science
Aggressively acquire and train new talent, maintaining a friendly and collaborative work environment, and develop future managers and leaders
Manage the development of predictive models to improve existing underwriting processes
Establish effective working relationships with all levels of staff and management
Develop strategies to help clients activate their analytics and create a more data-driven culture
Manages and develops a team of up to three data science and advanced analytics staff
Create and manage mix-marketing modeling and channel attribution modeling for forward thinking analysis

present

Los Angeles, CA

Senior Director, Data Science

Los Angeles, CA

Olson-Batz

present

Los Angeles, CA

Senior Director, Data Science

present

Establish partnerships with product and engineering teams and work closely with other teams
Work closely with data warehouse architects and software developers to generate seamless business intelligence solutions for business partners
Develops and communicates goals, strategies, tactics, project plans, timelines, and key performance metrics to reach goals
Creates and manages supporting and related business intelligence processes
Develop material and conduct training for both technical and business colleagues
Provide thought leadership and emerging quantitative fields where data science can play a significant role (i.e., computer visioning, context computing, etc.)
Provide technical mentorship to data scientists and guide technical thinking

Education Education

Bachelor’s Degree in Quantitative Field

Cornell University

Bachelor’s Degree in Quantitative Field

Skills Skills

History of Strong technical mentorship, managerial and leadership experience Strong organization skills, ownership and accountability
Strong analytical skills - the ability to accurately perform complex quantitative analyses and quickly learn new data management processes
Experience in sales, distribution, and/or marketing modeling highly desirable
Keen ability to visualize data through graphing/ charting/ information display skills (strong Power Point skills are essential)
Strong organizational skills and attention to detail
Strong communication and client service skills with CMO level roles and has the ability to explain complex concepts to diverse audiences
Strong understanding of big data concepts and knowledge of big data languages/tools such as Hive, Pig, Mahout or Spark (MLLib)
Strong ability to manage multiple projects for multiple stakeholders and manage expectations
Strong knowledge of the digital space and digital analytics including the vendors and testing methodologies and approaches
Excellent communication and presentation skills. Proven ability to interact with all levels of the organization including senior leadership and executives

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Senior Director, Data Science Resume Examples & Samples

Advanced subject matter expertise in retail industry, data modeling, analytical and reporting systems
Expert knowledge of complex analytical techniques including predictive modeling, optimization techniques, classification algorithms, decision trees, Bayesian networks, factor analysis, cluster analysis, data mining,
Proven experience in selecting and employing statistical methods to test hypotheses and develop insights
Working knowledge of one or more software development languages expected (Java, C, C++, C#, PHP, Perl)
Extensive knowledge of SQL and one or more of the following SAS, R, Matlab, S+, Stata
Proven ability to work with large data sets
Exceptional attention to detail; ensures deliverables are of high quality
Ability to build strong, collaborative working relationships with broad cross section of business partners
Strong oral and written presentation skills
10+ years of total work experience, with at least 5 years conducting ad hoc/exploratory business analyses using statistical tools
Experience in online or other direct marketing preferred

Director, Data Science Resume Examples & Samples

Play the role as the primary owner of the data science solutions to support company’s credit risk management initiatives as well as strategic data needs in other areas
Define big data strategies to utilize unstructured data for the development of business solutions
Process and organize various data sources with the objectives of gaining data-driven insights on business and operational performances
Study the usefulness and cost effectiveness of external big data sources and define strategies to use external big data sources
Work closely with other functions in the risk management area to optimize the data usage for the creation of advanced decision tools such as predictive models
7+ years’ of experience with data architecture and data analytics with 3+ years’ of experience in the credit or financial services areas
Advanced degree in computer science or related fields required, PhD a plus
Track record of designing and implementing big data solutions to support business strategies
Comprehensive knowledge and hands-on experience with Hadoop, Hive, MapReduce and/or HBase
Experience with latest database technologies such as NoSQL and RDBMS
Capability to architect highly scalable distributed systems, using different open source tools, and building high-performance algorithms
Familiarity with major big data solutions and products available in the market
Strong leadership and excellent communication skills. Recruiter: Ilana Raz

Director, Data Science Resume Examples & Samples

Building consensus internally & externally
Team building / mentoring
ROI Modeling & Media Optimization
Fractional attribution within digital space
Learning agendas & test design

Senior Director Data Science Resume Examples & Samples

Design, develop and deploy data-driven predictive models to solve business problems using the most appropriate techniques in data mining, machine learning, and statistical modeling
Find hidden gems that improve our understanding of customer behavior and drive decisions that improve OCF
Work closely with data warehouse architects and software developers to generate seamless business intelligence solutions for business partners
Comfort and experience with the art and science of extruding insight from massive, unstructured data sets

Director, Data Science Resume Examples & Samples

Design, develop and manage large scale, big data-driven predictive models that are integrated with key product features
Establish analytic standards and platforms that scale and can be leveraged in various initiatives throughout the organization
Ensure that testing and validation is a pervasive component of data science solutions
Deliver world class data-driven products in partnership with cross functional teams (Product Managers, Data Engineers, Software Engineers, etc)
Communicate complex concepts and the results of analyses in a clear and effective manner to senior management
Communicate with leaders to maximize the effectiveness of the data science team
Recruit talent and mentor the team as it grows
Ability to write production-grade code and learn new languages
Deep hands-on experience prototyping, building, releasing, and monitoring mission-critical machine learning models in high traffic applications
Command of principles of machine learning, statistical analysis, data mining algorithms, and mathematical segmentation and modeling
Strong understanding of big data concepts and knowledge of big data languages/tools such as Hive, Pig, Mahout or Spark (MLLib)
Experience with Amazon Web Services (or similar cloud services platform)
Experience with BI tools such as Tableau, Business Objects is a plus
Recent experience building Recommender Systems is a plus
Experience with machine learning in a distributed setting e.g. with Hadoop or Spark is a plus
Excellent communication skills. Equally adept at discussing data science solution details with an engineer or a business stakeholder
Success in leading a data science team
5+ years of experience

Director Data Science Resume Examples & Samples

PhD (preferred) or Master degree in Computer Science, Applied Mathematics, Statistics, Econometrics, Quantitative Social Sciences or related field
At least 8-12 years of experience depending on educational level and relevance
Leads development of analytical models using statistical, machine learning and data mining models. Defines model development tactics
Introduces new classes of business metrics
Defines feature engineering and extraction tactics
The Data Scientist collaborates with the data architects of various data platforms (big data, relational and non-relational) to define requirements for data architecture enhancements and new data ingestion
Utilizes Hadoop, SQL and NoSQL languages, tools and technologies to extract and process data for analytical needs. Designs and architects data processing pipelines
Utilizes Big Data Analytical tools and packages to build highly scalable analytical models
Leads the analysis and formalization of the business problems. Collaborated with business owners
Leading the team in adoption of new analytical algorithms, tools and technologies. Designs and implements new methodologies and algorithms
Stays up to date in understanding and contributes to the company and organization strategy

Director, Data Science Resume Examples & Samples

Thoroughly document the thinking and the details to enable future analysts to pick the work up
Identifies fact-based solution strategies for key business issues raised by clients to ensure that all important issues are addressed in fully and appropriately
Ensures business intelligence programs progress, status reviews, and corrective actions
Analytical and decisive Strategic thinker, flexible problem solver, great listener and team orientation
3+ years working within an enterprise data warehouse environment or Big Data architecture
6+ years of business experience in an advanced analytics role within marketing, research or similar groups
Comfortable working with large, complex data sources
Modeling and data mining within marketing
Advanced quantitative reasoning
Experience with Windows and UNIX/Linux operating systems

Director Data Science & Model Innovation Resume Examples & Samples

Work with large scale and complex traditional and non-traditional data sources to identify opportunities that enhance credit risk model performance. The Director will lead a team of Data Scientists who explore and examine data from multiple sources. The Director is responsible for discovering hidden insights within the data and evaluating alternate methods for using the data in an agile fashion. These models are used to originate new loans, manage existing customer risk, manage collection treatment and forecast loan loss provisions
Evaluate advancements in statistical analysis and model development methodologies and software. Work in collaboration with with Fintechs, consultants or new partnerships on big data & advanced analytics initiatives. The Director will foster partnership relationships to better understand advancements in the industry and how these changes could be used to transform current methodologies, tools and processes. He/she will use this knowledge to deploy innovative ideas that challenge existing assumptions and processes. The Director will communicate informed recommendations across the Global Risk Management structure
Ensure that the data used for model development is reliable and robust and that it adheres to Bank and industry standards. Leading the preparation and management of complex data is essential for ensuring model integrity. Strong understanding of business related characteristics, as well as proper handling of data anomalies and missing values are critical success factors
Identify, promote and lead process improvements including streamlining, automating, and standardizing data processes. Research best practices and propose innovations designed to enhance Risk Management’s ability to increase profitability and enhance customer experience. Build frameworks to test data used for risk models simultaneously
Thorough understanding of departmental goals and active participation in model development planning process. Provide consultative support to Senior Management, within and outside of Risk Management on initiatives pertaining to source data strengths/weaknesses
Provide strong leadership to direct reports to motivate both individual and team goals. Recruit a high potential model development team. Develop a top of class team in analytics and non-traditional data
Five+ years experience working in a major Financial Industry
Knowledge of building and validating credit risk predictive models with a deep understanding of data interactions combined with practical application
Knowledge of retail and small business credit policies, systems, and processes
Statistical software like SAS or R
Data structure and extraction techniques
Financial measures of risk/returns
The incumbent must be efficient and flexible as work is normally conducted under tight deadlines and with conflicting/multiple priorities. Excellent project management, problem solving, analytical and decision-making skills
Well-developed communication skills are required as internal and external presentations are frequent (e.g. at lenders/managers meetings, Executive presentations, partnerships etc.). Excellent written communication skills are also essential for preparing Executive proposals, management reports, and responding to field queries

Director Data Science Resume Examples & Samples

Highly contribute to data science team’s analytical agenda
Work with senior management across product, client, and IT divisions, taking a large role in driving that agenda with business units
Perform sophisticated, large-scale, and highly efficient analysis on markets, clients, and ecosystems and discuss client-facing analysis with clients
Brainstorm, design, gain approval, and implement internal and external tools and applications
Expand usage of Data Science tools broadly with staff and clients
Be a major contributor to the thought leadership interactions with business units and clients as it relates to client & market analytics
Drive the evolving enterprise-level data roadmap
Lead the team’s charge to achieve 10x-like enhancements
Provide and leverage feedback to improve the collaborative environment of the data science team from a communication and technical perspective
Encourage change that raises the profile of enterprise analysis, and drive change that revolutionizes how we use and visualize data
Be a major partner and contributor to enterprise-wide data/systems/analytical/software/hardware roadmap and prioritization decisions
Manage large, multi-faceted analytical projects, managing the tasks and resources to deliver valuable insight or capabilities
Use product and market knowledge to guide scoping discussions with business units and apply analytical skills to deliver results
Lead interactions with CD&S (Sales) and BLM (Product) teams to proliferate understanding, incorporate feedback, and refine team analytics
Lead and perform highly quantitative analysis on client and product market structures to identify and understand opportunities, risks, and trends
Make presentations to CD&S and BLM teams on analysis performed
Participate and lead client discussions and communicate analysis performed to inform clients and further their understanding of CME Group markets
Utilize technical skills to deliver systematic, automated, or statistically significant information with little initial human monitoring or intervention
Provide ideas for new alerts, determine the best methodology for delivery, and lead discussions to implement
Test out machine learning/deep learning algorithms to detect patterns
Stay current with leading edge systems, methods, and best practices for data science analytics, machine learning, and data infrastructure
Demonstrate core leadership capabilities as a project lead and as an individual to develop and support adjacent team members
BS/BA in Business, Engineering, Mathematics, Computer Science, or equivalent professional experience
MS in Applied Statistics, Statistics, Computer Science, or advanced Math, or Engineering (preferred)
Strong combination of business and technical/quantitative experience
2+ years of experience interacting with data in Apache Hadoop and Cloud Services (Amazon Web Services or Microsoft Azure)
8+ years of analytical or technical experience
2+ years of professional experience in finance or related fields
PhD candidates also encouraged to apply and may consider degree in place of other required work experience
Advanced skills in statistical programming and coding (e.g. Java, Python, R, SQL)
Strong skills associated with data base manipulation P/L SQL or equivalent
Advanced data analytics and modeling skills
Strong knowledge of capital markets, derivative products, and trading technologies
Strong communication and organizational skills
Ability to drive increased business value by adding expertise to business needs, translating and interpreting into analytical capabilities and IT requirements, and vice versa
Take initiative and provide leadership in all facets of the role
Not be afraid of hard work and doing things smarter

Senior Director, Data Science Resume Examples & Samples

Measurably impact business KPIs by delivering high quality scalable solutions
Discover actionable insights from data and present them through rich visualizations
Establish partnerships with product and engineering teams and work closely with other teams
Be responsible for design, implementation, deployment and support of key components of data science driven products
Recruit and interview top talent, as well as motivate, inspire, mentor and scale a team
Know and evangelize best practices in working with people, software and data
Propose and develop solutions independently and in collaboration with others
Assemble data sets from multi-terabyte structured and unstructured data repositories
Work on formulation, implementation, testing and validation of predictive models
Write high quality efficient code while implementing your own ideas
PhD in a quantitative discipline (e.g., statistics, computer science, physics), or MS with equivalent experience
10+ years of hands-on experience in analysis and modeling of large complex datasets
A passion for innovating with data sciences at scale – applying modern algorithms to massive datasets and creating measurable business value
Excellent interpersonal and communication skills, with a strong written and verbal presentation
Proven ability to take ownership of a project and lead R&D with minimal supervision
Track record of successful implementations of quantitative, data-driven products in a business environment
Ability to lead by example, foster collaboration, mentor and inspire others
Deep understanding and hands-on experience with optimization, data mining, machine learning or natural language processing techniques
Excellent understanding of algorithms, scalability and various tradeoffs in a Big Data setting
Expert level in R, Matlab or a similar environment; proficiency in SQL
Ability to personally put together a system of disjoint components that implements a working solution to the problem
Experience programming in at least one compiled language (C/C++ preferred)
Experience with real-time bidding, electronic trade execution or high-frequency trading algorithms
Experience analyzing internet scale sparse datasets (billions of rows, thousands of columns)
Expertise in using Hadoop and/or MPP databases (e.g., Netezza, Vertica, RedShift) for complex data assembly and transformation
Experience building and managing a team in a technology-oriented environment

Director, Data Science & Innovation Resume Examples & Samples

A strong passion to identify and solve real business problems using data
Entrepreneurial mindset to identify and promote innovative travel products, and solve the internal puzzles and prototype the end product
Excellent presentation skills to explain complicated analytical solutions to a non-technical group of people, internal or external
Ability to rapidly prototype and evaluate innovative travel products and applications
Hire and manage a global team of Data Scientists
Relocation will be considered for the right candidate**

Director, Data Science Resume Examples & Samples

Oversees development and usage of quantitative research tools and models to address client business problems and ensures that these tools are successfully deployed
Oversees program teams that develop and provide customer, product, and business operation insights, and analysis to improve and enhance companywide decision making
Ensures the effectiveness of projects, programs, and teams
Ensures the department implements and utilizes the industry best practices and technology required to provide insights, analysis and modelling for the company
6+ years working within an enterprise data warehouse environment or Big Data architecture
10+ years of experience in developing statistical targeting models using SAS and or R and or SPSS with Strong SQL skills a plus
10+ years of business experience in an advanced analytics role within marketing, research or similar groups

Director, Data Science Resume Examples & Samples

Leads development of analytical models using statistical, machine learning and data mining techniques
Defines model development tactics with knowledge of Big Data Analytical tools to build highly scalable models
Collaborates with the data architects of various data platforms (big data, relational and non-relational) to define requirements for data architecture enhancements and new data ingestion & storage schemas
Be a data science expert, leading the team in adoption of new tools and technologies
Lead outsourced and in-house matrixed team
Execute models & data science exploration aligned to product strategy; in turn, contribute back findings to advance product strategy and contribute new learning to the team
Build for cohesion: ability to build models out outputs that can be integrated back into the ad platform stack, working in tandem with the product team to design integration
Execute & measure: test models & outputs, tracking success and reporting back to the team
Minimum of 6 years of experience in applied project work - either in academia or professional setting
Experience with algorithm development, machine learning, data mining, recommendation engines, personalization, predictive modeling and natural language processing
SQL and advanced data processing
Advanced knowledge of at least on or more of the analytics languages/toolkits such as R, SAS, SPSS, Matlab or Python with analytical extensions
Proven curiosity: hackathons, passion projects, patents
Online advertising, marketing or Big Data experience preferred but not necessary
Ideally at least one programming/scripting language like Python, Scala, Julia, Ruby, or Java, C#, etc
Previous Leadership experience
Graduate Degree in Mathematics or Statistics, or other quantitative discipline

Senior Director, Data Science Resume Examples & Samples

Participate in developing overall company strategy
Build and refine predictive and descriptive statistical models to improve insights, enhance data-driven business strategies, and drive improved profitability
Build, review, and improve the actual code that solves complex data manipulation problems
Develop material and conduct training for both technical and business colleagues
Develops and communicates goals, strategies, tactics, project plans, timelines, and key performance metrics to reach goals
Develops and manages budget to ensure required resources are available
Graduate degree in quantitative field (e.g., mathematics, statistics, economics, and data sciences). PhD's preferred
Advanced statistical software user (SAS strongly preferred w/ SAS/STAT, SAS/MACRO, E- Miner)
6+ years of experience in developing statistical targeting models using SAS and or R and or SPSS with Strong SQL skills a plus
Strategic thinking and problem solving
Expert skills in SQL and experience in using databases from within SAS

Director, Data Science Resume Examples & Samples

10+ years of experience in Data Science, Marketing Analytics, Digital Marketing, or a business related fields
Strong knowledge of the digital space and digital analytics
Strong communication and client service skills
Management or mentorship experience - providing training, project support, career advice and delegated responsibilities
Proficiency in advanced analytical tools including: SAS, SQL or R
Proficiency in data visualization tools including: Tableau or Domo
Good understanding of advanced statistical techniques, including uplift modeling, logistic regression and cluster analysis
An understanding of master data management principles and data governance best practices
A good understanding of machine learning techniques and tools

Director, Data Science Resume Examples & Samples

8-15 years of work experience in a quantitative business environment
5+ years in marketing analytics
Strong knowledge of the digital space and digital analytics including the vendors and testing methodologies and approaches
Strong communication and client service skills with CMO level roles and has the ability to explain complex concepts to diverse audiences
Understanding of client's business models and how Razorfish can create custom solutions to support them

Director Data Science & Analytics Resume Examples & Samples

Leading team of Data Scientists to drive growth and improve performance of our products and services and well as improve performance of our manufacturing processes and sales & customer support processes
Leveraging your Data Science background to guide research and development of our modeling and categorization algorithms
Developing algorithms using Python, Java, and/or Scala
Collaborating with our HOS Gold Enterprise leaders, Engineering & Strategic Marketing to understand what’s currently possible, and what might be possible in the future (ideation) to drive growth and identify new product or service offerings
Establish Data offerings strategy for Aerospace Gold Enterprises and Functional organizations aligned to business STRAP & Breakthrough initiatives
Partner with our corporate Data Analytics team to drive collaboration and best practices across Honeywell
Work with corporate partners to establish scalable infrastructure to support data and analytics solutions
Ensure alignment with the Aerospace IOT COE and Data Governance & Data Management groups
Speaking at conferences, writing and contributing to scientific papers, and encouraging others to do the same
Self-starter with the drive to unlock the true power of big, noisy, messy, real-world data
You have extensive applied research or industry work experience in driving data monetization & bring new revenue generating solutions to market
Experience managing teams of Data Scientists, and believe they’re best motivated when they actively participate with the results of their work in production
Demonstrated experience working with multi-terabyte-sized data sets
Experience with modern data science tools such as Spark, Hadoop, Storm, etc
You know how to evaluate speed vs. quality tradeoffs in machine learning model

Director, Data Science Resume Examples & Samples

Develop and manage talent by identifying the skills and performance criteria necessary for success and working with their Senior Director to manage key projects and direct other team members to meet and exceed these standards as well as provide career-building opportunities for team
Work with the business to understand requirements, and use your software engineering, machine learning, and natural language processing expertise to make strategic recommendations to create solutions
Conceptualize analytic approaches, build out data sets and models for testing and production
Design, implement, and validate solutions in Apache Spark and Apache Hive, using Scala or Python on a large state-of-the-art cluster
Coordinate implementations working closely with engineering, to implement specific solutions into Conversant’s platform
Measure success and provide feedback, and monitor launch effectiveness of new initiatives
Identify requirements for future research focus in their key area
Experience with Computer Vision, Information Retrieval, or Recommender Systems
Experience with SQL, Scala, Python, or Java

Senior Director, Data Science & Engineering Resume Examples & Samples

Build, manage, and create the strategic vision and executional roadmap for the department’s new Data Strategy and Innovation team
Work closely with the SVP, 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
Develop out an aligned data strategy that connects key stakeholders across the company (which includes but not limited to the below)
10+ 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
BA/BS (MS or Ph.D. preferred) in statistics, computer science, data engineering, quantitative theory preferred
Hands-on experience and expertise in Python, R, SAS, SPSS, SQL, Spark, and other related analytical/programming tools and software
Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
Track record of creating / building / architecting data delivery automation, data dashboards, data platforms
Moderate knowledge of Big Data querying tools, such as Pig, Hive, and Impala
Experience with AWS for streaming data
Experience working with different types of data: measurement data (e.g., Nielsen, Comscore, Rentrak), other syndicated data (e.g., Symphony AM, MRI, Simmons), survey data, social data
Hands-on experience in using data reporting/visualization software such as Tableau, Tibco Spotfire, Domo
Proficient understanding of distributed computing principles
Ability to solve any ongoing issues with operating a distributed cluster architectureExperience with Scala
Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
Knowledge of various ETL techniques and frameworks, such as Flume
Experience with various messaging systems, such as Kafka or RabbitMQ
Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O
Effective verbal and written communication skills to be able to work successfully with key stakeholders, and drive enthusiasm and adoption of new products
Strong team player, leader, manager, mentor, and positive catalyst
Ability to multi-task, work under deadlines, within a very dynamic, fast-paced, and forward thinking environment

Director, Data Science Competency Leader Resume Examples & Samples

Experience of statistical and data mining techniques, which may include some of the following: regressions models, cross section time series models, longitudinal data analysis, Structural Equations Models, formulating and solving OR models like linear (large-scale), mixed integer, text mining, natural language processing, non-linear and evolutionary programming methods, and various Clustering algorithms
Understand and able to research leading trends related to data analytics, data modeling, big data and data lake technology, and data virtualization and aggregation, and develop strategic points of view on applicability to Merck’s business
An analytical problem solver: Strong analytical and problem-solving skills, and ability to work with incomplete or imperfect data
Persistent and driven: Demonstrated characteristics of a forward thinker and self-motivator that thrives on new challenges and adapts to learning new knowledge. Natural curiosity and a desire to do things differently
Collaborative: demonstrated experience applying excellent oral and written communication and interpersonal skills working with global and cross-functional teams towards common goals, realizing that the best results from the combined efforts of diverse teams
10 years of experience
Experience with health care, consulting or cross-industry exposure
Ability to develop relationships and communication with people at all levels of the organization (both technical and non-technical)
Demonstrated success working with senior executives including C-level

Director, Data Science & Emerging Technology Resume Examples & Samples

A Bachelor’s Degree is required with a Master’s Degree or PhD preferred
Must possess a minimum of 15 years of broad IT experience required, preferably in a large, global organization
Previous experience with technologies such as Pivotal HAWQ, Matlab, Python, and R is required
Global experiences with good understanding of regional differences across ASPAC, EMEA, and North/South America in implementing IT solutions is highly preferred
Strong project leadership and coordination skills, with the ability to manage multiple projects of varying sizes and priorities is required
Sound understanding of big data solutions, capabilities and components and how technologies complement one other is required
Ability to prepare/provide value driven impact of solutions/technologies to influence the business and the financial proof of value of any solution/technology required
Understanding of advanced business analytics technologies and methods is required
Experience with cloud based services offering including but not limited to Amazon Web Services and Microsoft Azure is highly preferred
Experience with Big Data technology stacks such as AWS/EMR, Cloudera and Hortonworks is highly preferred
Experience with Gemfire technology is preferredArchitecture

Director, Data Science Resume Examples & Samples

Act as Data Science contact and liaison for all Data Science related methodology and execution to leadershipEnsures Data Science services are delivered to the highest quality standards
Provides expert technical consultation with internal and external clients and solves complex Data Science-related issues
Drives the roll out of new or enhanced services providing an integrated statistical vision
Guides the correct use of reported data through client engagement and content for client training
Reviews on a regular basis the statistical quality of our services
Reviews with Operations, the quality of data collection and sample requirements as well as opportunities for quality improvement
Gathers and implements client requirements from commercial teams and Product Leadership
Turn numbers into stories that clients can understand
Collaborates with cross-functional teams to provide a professional, clear response to all clients
Represents the company with academic and industry contacts and councils
Identifies and develops top talent and leads teams
Oversees team budget
Maintains /creates internal and external methodology whitepapers and documents
Manages team of 3-5 direct reports
Bachelors degree in Statistics, Social Science, Operation Research, or other hard sciences (e.g. Engineering, Computer Science, Biology, Physics etc.) Masters degree preferred
8+ years experience
Experience working in Advertising, Market or Survey Research
Outstanding analytical expertise
Excellent leadership and people management skills
Excellent presentation skills for internal and external clients
Embodies the Nielsen Leadership values (e.g. diversity, inclusiveness, integrity, etc.)
Assesses situations quickly and act with agility
Advanced proficiency in data analysis, statistical methods, and methodologies
Ability to work cross-functionally and energize, empower and influence at all levels (both internal and external)
Experience working in support of Media or Advertising Effectiveness industry clients or services - preferred
Proficiency with Statistical Software – preferably Python or R - preferred

Director Data Science Resume Examples & Samples

Working with client stakeholders (retailers and their agencies), your client analysts, ODC’s solutions team, product strategy team, and data science R&D team as needed to develop analytic plans to measure a wide variety of digital campaigns. Plans include data requirements, analytic approach and timing. For complex campaigns, this planning takes place at the campaign planning stage to ensure plans are set up to enable successful post campaign measurement
Work with client analysts to assess and balance workload and ensure timely delivery of analytic results
Develop and deliver impactful presentations that communicate analytical findings in an intuitive manner and help clients and our solutions team apply learnings to future digital marketing efforts. Strong client presence, credibility and leadership are key, as you will be presenting to a wide range of functions and levels, from managers to C-suite
Develop a deep understanding of the methodology behind our sophisticated measurement models to provide a causal sales lift for digital advertising campaigns. Lead methodology review sessions with key clients, and participate in internal efforts to further customize approach and deliverables to the CPG Retail vertical
Identify opportunities to improve internal efficiency via our integration with other teams/tools. Support and/or develop processes to manage communication/timelines, support revenue reporting, etc
Lead and develop your team of analysts, with a focus on growing skill sets and expertise and creating a productive and supportive team
Identify opportunities to leverage traditional loyalty-based analytics (core skill set of CT-based Regional Retail analytics team) into the digital analytics space for national, digitally-focused CPG Retail clients
Serve as connection point and “ambassador” for the CT-based and remote CPG Retail Client Analytics team with other CO-based Data Science, Go to Market, Product, and Operations team. Your presence in ODC’s Westminster CO-based headquarters is key to your ability to fulfill this need; location is thus not negotiable
Travel regularly to key clients to present results and participate in planning and methodology review sessions. Maintain an occasional presence (1-2 x per month depending on other travel) in the CT office. Present occasionally at industry conferences as appropriate. Travel will be 25-50% on average, varying week to week based on client needs
10+ years of demonstrated success in the field of marketing analytics, media analytics, marketing research, or analytic function at a leading CPG Retailer. Experience in the digital media space, including analysis of online consumer behavioral data, targeting, digital measurement and/or attribution, etc. highly preferred
Experience leading an analytic team that works with large datasets (billions of records), with experience in a wide range of technical skill sets (stats, R, Python, SQL, etc.). Exceptional problem solving skills with unrelenting focus on practical business implications
Exemplary project management skills and proven ability to multitask in a fast-paced environment
Ability to work in a demanding, fast-paced and dynamic work environment
Demonstrated success in driving successful client and business outcomes in an environment where multiple stakeholders have separate interests and objectives. Collaborative, team-oriented mindset balanced with a high drive for results
Ability to both “roll up the sleeves” and dig into details when needed, and see/drive towards “big picture” vision
BS in statistics, mathematics or similar quantitative field. Graduate degree in marketing, analytics, data science or MBA preferred but not required

Director, Data Science Resume Examples & Samples

Oversees development and usage of predictive models to address client business problems and ensures that these tools are successfully deployed
6+ years working within an enterprise data warehouse environment or big data architecture
10+ years of experience in developing statistical targeting models using SAS and or R and or SPSS and strong SQL skills
Strong ability to manage multiple projects for multiple stakeholders and manage expectations

L Oreal , Director Data Science Resume Examples & Samples

Lead in the transformation of data-driven decision making in marketing to include predictive analytics
Deliver on innovating and refining measurement methodologies for marketing that address broad and narrow business objectives
Drives performance against business objectives which include, but are not limited to: growing revenue, growing share, increasing profitability
Develop analytical road map that integrates modelling and predictive analytics into current and new business intelligence activities
Collaborate closely with Digital IT to govern and help facilitate best practices in: Data Collection, Governance, and Hygiene
Collaborate closely with Data Team to identify new sources of data relevant for modelling business outcomes
Lead in the following analytical projects, but are not limited to: Product Recommendation Engines, Targeting Segmentation, Predictive Consumer Behavior Models
Improvements to product and content search and sorting
Prediction of subscriber churn, sample conversion, shop activation, etc
Evangelize Data-Influenced Decision Making within the broader organization via education, presentations, 1-on-1 conversations, etc
At least 3-5 years of relevant experience; Preferably 1 year of management experience
Strong understanding of retail (e-commerce, brick & mortar, indirect selling through wholesale
Hands-On Experience in the following areas

Director Data Science Resume Examples & Samples

Lead data science team including internal and external data scientists, PhD and master students
Master the full cycle of advanced, cutting-edge analyses: from understanding/framing the business need to embed your deliverables into operational processes
Design, develop and manage our data science platform for creating personalized experience for our consumers across all digital communication touchpoint
Design, manage, and deliver end-to-end analyses aiming at helping Marketing to improve the experience of our consumer, find the most relevant contents to him, increase his engagement and conversion, or realize his value
Leverage different forms of analytical applications such as data discovery, customer profiling, customer segmentations, predictive modelling, design of experiments (inferential statistics), post-action measurement, what-if analysis, etc
Build advanced predictive models and embed intelligence into different marketing and communication channels (e.g. Web personalization and optimized targeting through different communication channels email, Website, Mobile, paid media, etc.)
Constantly monitor the ecosystem of data science/big data, maintain solid network with the key players, remain on the edge of your Data Scientist skills
Outstanding analytical skills that demonstrated a hands-on ability to generate actionable insight out of Big Data
Ability to work in a fast-paced and complex environment with a large diversity of stakeholders
Understanding of fields related to your activity (Market research, Web analytics, Retail analytics, media analytics) to leverage synergies and work towards the building of a 360° view of our consumers

Senior Director, Data Science Engineering Resume Examples & Samples

Manage all aspects of dataset creation and curation, including the frameworks to derive metrics from Hadoop and Oracle EDW systems
Build and own the automation and monitoring frameworks that showcase reliable, accurate, easy-to-understand metrics and KPIs to stakeholders
Drive data innovation for all internal use cases pushing the envelope on scalability and technology ensembles to leverage best of breed (internal, open source, and external technology)

Associate Director, Data Science Resume Examples & Samples

8-10 years of experience in Data Science, Marketing Analytics, Digital Marketing, or a business related fields
Bachelor’s degree, in Marketing, Business, Engineering or a related field. MBA preferred
Strong consultative skills and the ability to challenge status quo and gain adoption
Comfort with working in and contributing to a fast-paced, team based environment
Expertise in leading implementations of marketing platforms including: Adobe, Google, Salesforce, Oracle or IBM. Emphasis on their analytics, campaign and testing capabilities
Proven ability to influence stakeholder and senior leaders, and manage organizational change

Director, Data Science Resume Examples & Samples

Develops overall strategy and directs execution of data science departmental activities
Prepares and maintains long-range plans in support of needs of the business unit/s or functions served
Provides expertise and support to identify, define and solve a variety of problems through data mining, discovery, modeling and analysis to support various operational and corporate initiatives
Consults with business partners to understand, align and deliver data analytic work products to support business objectives and priorities
Builds, maintains and directs functional and/or technical teams to develop and implement high value business solutions
Establishes and communicates common goal and direction for the department
Presents and communicates information to all levels of the organization (including
Develops departmental budget and resource plans
Serves as a liaison to key business stakeholders, senior executive management, and core information systems leadership
Provides and/or monitors administration of training and mentoring to less
Strong analytical skills and knowledge and understanding in identifying root causes of problems, create and implement effective practical solutions for business operations based on data analysis
Experience in Ieading and working as part of an integrated solution development team to provide value through data science and data product development
Practical knowledge and demonstrated experience in mathematical, statistical models and methods, large scale data sets, advanced data mining analytical role
Employee management and development
Program and project management, budget development, and monitoring
Organizational change and development
Excellent communication and presentation skills. Proven ability to interact with all levels of the organization including senior leadership and executives
Ability to present information, analysis, ideas, and positions in a clear and convincing manner to both technical and nontechnical audiences
Ability to lead a group to consensus, solve problems, and accomplish tasks
Ability to multi-task, meet deadlines, and anticipate needs along with ability to operate and promote an environment of teamwork
History of Strong technical mentorship, managerial and leadership experience Strong organization skills, ownership and accountability
Ability to work in fast-paced environment
Mastery of programming and scientific computation (Python, R) and data visualization
Knowledge of Big Data, SQL programming
Knowledge and experience working in SAS toolsets
Required to use motor coordination with finger dexterity (such as keyboarding, machine operation, etc) most of the work day

Assistant Director, Data Science Resume Examples & Samples

Develop appropriate statistical and machine learning approaches to customer selection, workflow optimization, cross/up selling, and other challenging problems central to our business
Define and validate complex primary datasets used to train and evaluate predictive models
Establish and employ measures, metrics, visualizations, and tools to evaluate statistical models
Work in a collaborative team environment with other highly skilled specialists in insurance, statistics, machine learning and technology
Research new modeling algorithms, languages, packages, and statistical tools to enhance the overall productivity of the team
Design market experiments and pilots designed to test hypothesis
Communicate with team members, developers, and leaders in clear language with data visualizations
Master's Degree in Mathematics, Economics, Statistics or any other quantitative field plus a minimum 5 years of applied business / non-academic experience preferred
For non-Masters Degree candidates, Bachelor's Degree and minimum of 7 years of applied business/non-academic experience, or equivalent is required
Proficient in predictive analytics including real-world experience in model validation, testing and deployment
Experienced in the following: generalized linear models, dimensionality reduction, clustering, and Bayesian approaches to data analysis
Expert SQL skills
Proficient with at least one language for data analysis, such as R, Python or SAS
Proficient with at least one package for reporting/visualization of data, such as Rstudio’s Shiny, or MicroStrategy
Educational training with machine learning technologies
Exceptional planning, analytical, decision-making, communication and project management skills

Director, Data Science Resume Examples & Samples

Build predictive models using GLM, CART, logistic regression, machine learning and other means, in support of implementation of new rating plans and other initiatives
Validate, manipulate and perform exploratory data analysis tasks on analytical data sets. Utilize Hadoop and other Analytic Computing Environments to work with “big data”
Provide qualitative and quantitative data support to ensure accuracy of characteristics and metrics. Analyze new data sources for availability and quality, and integrate with internal sources to support research or analytics. Build repeatable processes
Test and evaluate new software and methodologies
Regular communication with Predictive Analytics team and business partners
Peer review and evaluate models built by research staff
Advanced knowledge of statistical modeling techniques and tools
Strong programming experience within at least one of SAS, R or Python
Experience with other statistical analysis packages (R, Matlab, SPSS, etc.)
Experience with handling large datasets in array based query processing (Hadoop, SciDB, etc.)
Strong understanding of the Personal Lines business and the pricing of related insurance products
Ability to work independently as well as part of a team; builds effective relationships
Critical thinking

Director, Data Science Resume Examples & Samples

Conduct root cause analysis on performance and make recommendations based on advanced analytics findings of site experiences / customer paths, campaigns, site design/creative changes to optimize conversion and revenue
Conduct cross-channel digital ROI Analytics and make recommendations for marketing/site/store ROI improvement, spending optimization as well as retention programs and targeting
Create and manage mix-marketing modeling and channel attribution modeling for forward thinking analysis
Serve as a team expert in digital analytics spanning Web, Mobile, Social, Email and Media. Leading efforts in the integration of social insights, listening platforms with online behavioral reporting and ecommerce metrics
Develop innovative approaches to data-driven targeting strategies that drive measurable results, uncovering opportunities to reduce attrition, improve cross-sell, and enhance targeting of existing and prospective customers
Become the Subject Matter Expert on performance of sales, service and support interactions / customer journeys across desktop/mobile site experiences and mobile app
Develop close rate analysis for existing and prospect customers to measure customer probability to order/upgrade service and then leverage outputs from the analysis combined with digital and cross-channel customer path/journey analysis to generate recommendations to improve close rates
Perform analysis to identify digital actions/events/interactions which result in increases/decreases in revenue and Churn and leverage insights / real-time analysis on these unique sequences of actions/events/interactions to identify opportunities to proactively drive site changes / personalization to increase revenue and decrease churn from acquisition through the Customer tenure
Analyzing digital marketing performance based on customer, channel and product to developed segmentation approaches for improved targeting and customer experience
Ensure campaign and marketing program elements are accurately aligned, tested and implemented
Build and refine predictive models that improve insights, strategies, drive conversion, retention and profitability
Discover new opportunities to optimize the business through analytics and predictive modeling using business analytical tools and implement site optimization recommendations based on historical/current data
Recommend contact optimization strategies to maximize revenue and profit
6+ years of relevant professional experience conducting digital analytics or analytical experience with a demonstrated passion for digital
6+ years working within large enterprise data warehouse environment or big data architecture
6+ years of experience in developing statistical, machine learning models using Python/R/Spark/Scala/SAS
Graduate degree in quantitative field (statistics, economics, and data sciences). PhD's preferred
Experience with site testing and personalization tools a plus
Proficiency with e-commerce or content management systems highly preferred
Experience with tag management solutions (Tealium, Ensighten, Google Tag Manager, DTM etc.)
Advanced data mining and predictive modeling skills (regression, segmentation, Bayesian, boosting)
Strong communication skills and experience managing multiple projects while managing expectations
Be familiar with SEO/SEM best practices and online program management
Team player with ability to work well in a cross-functional team environment
Ability to work effectively with diverse teams including statistical, technical, creative and marketing resources
Strong leadership experience and proven ability to drive results, positively influence change, and motivate others within a non-direct reporting structure to take action/execute

Director, Data Science Junior Resume Examples & Samples

Work closely with Strategy & Marketing as well as IS teams to collaboratively assess, understand improve and deliver rich data content for analysis
Thorough understanding of data gathering, storing, and retrieval methods. Combine the disparate data sources to generate very unique market, industry and customer insights
Comfort with visual art and design to turn statistical and computational analysis into user-friendly graphs, charts, and animations. Create insightful data visualizations (e.g., motion charts, word maps) that highlight trends
Accountable for data validation, consolidation and cleansing processes
Performs related duties as assigned or requested. Some of these include
Serve as a liaison to Business
Translates data insights into Business Consumable insights
Manages Projects
Performs Cross Functional Team Management
Builds storyboards
Builds Simple Tableau / QlikView dashboards to for consumable insights
Learns the data science model development process and help out by owning work threads or work streams
Does smell tests of results, insights and helps with QC of the process, data, insights
Builds optimization and scenario analysis models
Builds macros in Excel other languages to streamline delivery
Builds and oversees the building of scoring engines
Helps with building of Business Cases before initiating project

Director Data Science Resume Examples & Samples

Leverage different forms of analytical applications such as data discovery, customer profiling, customer segmentations, predictive modelling, design of experiments (inferential statistics), post-action measurement, what-if analysis, etc…
A minimum of 8 years professional experience in data science and analytic role , 2 – 4 years CRM / consumer profiling focus, 2-4 years leadership ( people or project management experience)
Excellent coding skills using common data science toolkits, such as SAS, R, Weka, Python, Spark, git, linux/ unix
Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Hadoop, Hive, SQL or noSQL experience , Scala, in memory data bases HANA, exasol
Experience in developing Customer profiles, CLTV, attribution model, lookalike modeling, clustering, and classification and segmentation models on large and sparse data sets

Senior Director, Data Science Resume Examples & Samples

Dive into large, noisy, and complex real-world behavioral data to produce innovative analysis of historical patterns in customer behaviors and product performance
Assume ownership for analysis projects from data modeling to final delivery
Collaborate with business owners and teammates to solve business problems, which may include standard tool or custom algorithm development
Ensure that the required types, history, and granularity of data is captured to support analytic needs and opportunities
Deep knowledge of analytic methodologies such as regression, signal processing, optimization, machine learning, data mining, etc
Strong working knowledge of data mining algorithms such as decision trees, probability networks, association rules, clustering, regression, and neural networks
Experience with analytics packages SAS, SPSS, Matlab, R, Weka etc
Creativity to go beyond current tools to deliver best solution to the problem
Good understanding of high-level product architecture and data flow patterns
12+ years working experience
Direct, personal experience analyzing massive unstructured data sets
Experience in telecommunications, internet, ecommerce, or media, preferred

Director, Data Science Resume Examples & Samples

Work collaboratively with actuaries, data analysts, clinicians, and operators to identify opportunities to add value through advanced analytics
Integrate disparate data sets, conduct exploratory analysis, and produce actionable insights for clinical intervention and risk-based contracting
Help drive the development of next-generation reporting and BI tools, working closely with internal IT teammates and external vendors
Design and implement predictive models to project patient outcomes dependent on demographic and clinical care variables
Storyboard, stress test, and articulate arguments to key decision-makers
Enhance data visualization capabilities to communicate findings from complex analyses
Serve as in-house data expert and teach data science techniques to fellow teammates
Performance-based rewards for stellar individual and team contributions
Dedication, above all, to caring for patients suffering from chronic kidney disease across the nation
Dedication, above all, to caring for patients suffering from chronic kidney failure across the nation
Advanced degree (Masters or higher) preferred in applied math, statistics, computer science, or related field
Minimum three years of experience integrating disparate data sets and producing statistical analyses using SAS, SPSS, R, or other programs
Experience in healthcare, specifically analyzing medical claims and clinical data
Experience with SQL and managing relational databases including
Commitment to DaVita's values of Service Excellence, Integrity, Team, Continuous Improvement, Accountability, Fulfillment and Fun
Effective communication skills - verbal and written
Strong analytical skills - the ability to accurately perform complex quantitative analyses and quickly learn new data management processes
Focus on analytical process improvement
Energetic team player
Confident self-starter with positive attitude and drive
Ability to multi-task and consistently meet deadlines
Problem solver who works well independently
Successful candidates will have interest and strengths in competitive strategy and innovation

Director, Data Science Resume Examples & Samples

Work with VP of eCommerce and Innovation to develop and deliver the vision of a data science driven – enterprise
Lead advanced analytic team in exploiting data in an effort to promote growth and business development via deep data mining analysis
Develop and implement strategies to leverage data science for each stage of customer lifecycle marketing
Develop and implement various types of predictive models, segmentation strategies, optimization algorithms, and data mining analyses with a targeted result of increasing revenue
Drive multi-channel analytics for online and integrated online/offline contexts
Incorporate best-in-class data science driven approaches and tools to improve prospect targeting, new customer acquisition and delivering personalized online experience
Partner with IT partners to develop single source of truth data warehouse to improve decision-making and speed-to-market
Develop and lead the rapid test-and-learn team to improve every aspect of digital marketing and eCommerce
Lead the development of the Big Data Center of Excellence to develop Big Data IT and organization infrastructure to drive transformation
Perform R & D on new innovative analytic techniques
Summarize and present analyses to Marketers, Merchants, Vendors, and Executives

Director, Data Science Resume Examples & Samples

Influence the course of the business as a trusted advisor to business leaders and users, using data and analytics as a basis for better, more informed decision making
Masters or PhD in business analytics or related field, or equivalent experience
10+ years of experience in solving analytical problems using quantitative approaches (or equivalent)
Proven success leading, managing or mentoring a team of analytic professionals
Demonstrated leadership using statistical analysis and research to drive positive change in a business setting
Brand, product development, marketing, media or advertising agency experience (preferred)
Clever and curious with a passion for finding insights in data and using quantitative analysis to answer complex questions
Experience with mapping business drivers to data mining and analysis approaches
Strong analytical and data fluency skills
Driven self-starter with an appetite for new challenges
Creative problem solver with a common sense and practical solutions orientation; must be passionate about the role analytics plays in improving business performance
Proven leadership ability and evidence of positively influencing cross-functional teams
Excellent verbal, written, and presentation skills demonstrating an ability to "tell a story"
Ability to work with diverse teams (Sales, Research and Developers) to convert product ideas into requirements for analysis
Understanding of market research or analytics, and its application to broadcast and/or digital media (preferred)
Strong entrepreneurial spirit; high energy level, sense of urgency, responsive, confident, thorough, not afraid to make decisions
Strong work ethic; ability to overcome setbacks and enthusiastically persist until ambitious goals are achieved; must be resourceful, creative and innovative
Results oriented team player that leads by example, holding him or herself accountable for performance, takes ownership, champions efforts with enthusiasm and conviction

Director, Data Science Resume Examples & Samples

Manages and develops a team of up to three data science and advanced analytics staff
Collaborate with other business partners to develop appropriate statistical approaches and tools that will drive strategic decision making related to reserving, trends and other challenging problems central to our business
Understand the competitive marketplace, business issues, and data challenges in order to deliver actionable insights, recommendations and business processes
Research, recommend, and implement new and/or alternative statistical and other mathematical methodologies appropriate for the given model or analysis
Supervise and perform highly complex, technical and creative predictive analytics projects
Provide tactical input on highly technically complex projects that drive change across function, SBU or Corporate Department
Present findings, share insights, and make recommendations that impact profitability, growth and/or customer satisfaction
Regularly engage with the data science and actuarial communities and lead cross-functional working groups
Competencies typically acquired through Master’s degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 5 years of applied business/non-academic experience, or Ph.D plus minimum of 3 years of experience. Insurance or financial services industry experience preferred
Proficient in predictive analytics including real-world experience in model development, validation, and testing
Experienced in the following: generalized linear models, survival models, random forests, clustering, and Bayesian approaches to data analysis
Proven ability to lead and drive projects and assignments to completion through others, and effectively engage talent
Ability to establish and build relationships within and outside the organization
Basic knowledge of insurance principles, underwriting and ratemaking concepts and the various functions of an insurance organization, including Finance, Underwriting, Sales and Claims desirable
Ability to give effective presentations to management and other groups

Director, Data Science Resume Examples & Samples

Support advanced analytics and statistical analytic needs across the firm including but not limited too
Extracting insights from large unstructured databases
Develop/maintain insight/recommendation engines
Client life time value analysis and modeling
Statistical and behavioral segmentation efforts
Predictive modeling for acquisition and retention of clients/assets
Effectiveness/ROI analysis of major firm initiatives
Geo-spacial analysis
Establish the Vision and Annual Objectives of the team, identifying key roles and responsibilities and goals and the completion of major department initiatives
Provide leadership, development, and mentoring to k\leaders and associates through examples and timely feedback
Complete understanding of internal systems and consultation with technology leaders to improve the communication and deployment of effective and efficient solutions
Consistent and continuous evaluation of the department's activities and controls to ensure we are meeting the Vision and the Goals
Supervision and establishment of key measures for the area
10+ years in an advanced analytic consulting role
5+ years in a leadership role
Outstanding oral and written communication skills. Ability to communicate the integration between business goal, analysis and the results
Ability to influence senior management
High level interpersonal skills
High level consulting skills to uncover the key business questions and persusively articulate recommend next steps/actions
High level people and project leadership ability
Communicate complicated techniques in simple English to non-technical partners
Abilitity/farmilarity with data science scripting languages, Python, R, SAS, Spark, Scala, SQL, etc
Solid understanding of machine learning techniques, regression modeling (including logistic, survival, and GLIM family)
Experience with Hadoop and hadoop tools like Hive, Impala, Python
Ability to translate data into meaningful value propositions for clients in order to facilitate understanding

Director, Data Science Resume Examples & Samples

Search for new variables and approaches that improve the pricing segmentation and underwriting guidance
Partner with the business to ensure alignment between our models and business objectives
Communicate changes, impacts, and next steps while anticipating intuitive questions
Manage a team of data scientists

Director, Data Science Resume Examples & Samples

Ph.D. or Master’s Degree in a quantitative discipline (Statistics, Applied Mathematics, Computer Science, Electrical Engineering, Physics, etc.)
Seven plus years developing of probabilistic models and machine learning algorithms including real world experience in model development validation and testing
Expert in data analysis using Python, R, SQL or SAS
Demonstrated data transformation and manipulation experience
Proficient with any of the data science methodologies including GLM, clustering, random forests, survival analysis, SVM, text mining, neural network and Bayesian analysis
Knowledge of NoSQL systems, Hadoop/map-reduce, Spark, Hbase, etc
Proven ability lead and drive projects and assignments to completion
Experience in sales, distribution, and/or marketing modeling highly desirable
Financial services industry experience preferred
Experience with Big Data platform preferred

Director, Data Science Technologies Resume Examples & Samples

Masters degree in Electrical Engineering, Computer Science, Data Science, Mechanical Engineering, Industrial Engineering, Applied Mathematics or Statistics
7 years of experience leading people
Proven track record of building organizational capability and talent through effective recruiting, training, coaching, development and optimizing organizational structure
Basic understanding of legal matters dealing with intellectual property, government contracts and other research agreements
Direct international experience leading high performance technology based organizations is highly desirable
Ideal candidate will also have deep understanding of advanced controls methods in complex industrial systems with both dynamical and finite states. Deep understanding of software-enabled and embedded controls development issues, especially in the context of model-based and hardware-in-loop control algorithm and software development processes. Working experience with decision algorithms, statistical classification methodologies, sensing, data aggregation, information fusion and optimization methodologies

Director, Data Science Resume Examples & Samples

Manage team of 10-12 data scientists to provided leading-edge solutions to big data challenges
Work collaboratively with senior management to develop strategy and approach to defining business challenges to be answered by data science
Collaborate with analysts, product managers, engineers and operations to build exceptional, data-driven products
Provide industry thought-leadership and support external communication initiatives
Provide leadership to data science team to analyze large data sets to extract actionable insights, apply machine learning at scale to predict audience behavior and consumption of digital media and develop tailored algorithms for large scale nonlinear optimization problems
Insure data science organization practices meticulous validation to ensure high data cleanliness and quality
Communicate analysis and discoveries to team members and customers
Think creatively and propose new directions and questions to pursue
PhD in quantitative field (computer science, statistics, physics, chemistry, biology, etc.) is preferred but exceptional MS candidates will be considered
Experience in managing and leading expert data science teams
Demonstrated thought-leadership both internally and externally
Publication in relevant media and marketing trade magazines and academic journals
Experience in data mining and machine learning techniques such as clustering, pattern discovery, neural networks, decision trees, etc
Experience using statistical packages in python or R
Familiarity with distributed computing infrastructures such as Hadoop/Spark

Director Data Science & Engineering Resume Examples & Samples

Experience deploying algorithms in a production environment
Experience with Machine Learning: Support Vector Machines, Random Forests, Decision Trees
Ability to work with technical and business-oriented teams
Ability to work with non-technical resources on the team to translate data needs into Big Data solutions using the appropriate tools
Experience working with very large data sets, knows how to build programs that leverage the parallel capabilities of Hadoop and MPP platforms
Experience designing and delivering services-based solutions on Hadoop

Director, Data Science Resume Examples & Samples

Develop and continually advance naviHealth’s decision support tools for clinical workflow, Post-Acute Care management, and related business needs
Employ structured approach to leveraging large data sets to uncover new business insights that will support the evolution of our products and services
Apply demonstrable statistical, machine learning, and business strategy experience to develop and support predictive algorithms and related decision support products
Create examples, prototypes, visualizations or demonstrations to help leadership better understand the work and recommendations
Provide thought leadership, conduct studies, and publish whitepapers and articles in trade and scholarly journals
Collaborate with other business functions such as clinical services, product management, customer implementation to define, prioritize, develop, and implement data science products
Continually monitor and work with stakeholder to gather feedback and identify opportunities for ongoing improvement
Build and manage a Data Science team as determined by business needs and growth opportunities
Establish effective working relationships with all levels of staff and management
Promote a culture of transparency, communications, and collaboration
Measure and report on performance of Data Science team
Master’s degree in Statistics/Computer Science/Software Engineering; PhD preferred
8+ years’ demonstrable experience developing solutions using machine learning techniques and applied statistical analysis such as regression, classification, clustering, Naïve Bayes, decision forests
Expert-level experience in data science and visualization toolkits such as R, SAS, Tableau
Experience with relational, OLTP, SQL, dimensional and OLAP databases and technologies, business intelligence, data warehousing, and ETL database technologies and solutions
Strong project leadership and management skills required; ability to prioritize, plan, and handle multiple tasks/demands simultaneously
Strong written, verbal, and visual communications skills required
Team-first orientation: must thrive in collaborative, team-based work environment
Experience with staff development and training
Passion for creating new products that drive significant value for our clients
Intellectual curiosity and creativity: thrives in developing new ideas and identifying growth opportunities
Strong problem solving, conflict resolution and negotiation skills
Strong stakeholder engagement skills and detail orientation

Associate Director, Data Science Resume Examples & Samples

8+ years of experience in Data Science, Marketing Analytics, Digital Marketing, or a business related fields
Bachelor’s degree, in Marketing, Business, Engineering or a related field
LI-SNNA

Director Data Science Resume Examples & Samples

Apply advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems
Provide qualitative and quantitative data support to ensure accuracy of characteristics and metrics. Build repeatable processes
Provide expertise on mathematical concepts and inspire the adoption of advanced analytics and data science across the breath of the organization
Strong strategic thinking and exceptional analytical capability
Strong verbal/written communication skills; Must be able to communicate effectively at all levels across the organization

Practice Director, Data Science Resume Examples & Samples

Lead and manage a team of experts and senior consultants at the regional level within a specific practice domain with focus on incubation of new business opportunity areas, community leadership, IP development and capture, repeatable offerings, and support of the Sales teams
Partner with other Region and GEO Practice Directors to execute our mission to drive revenue through a business outcome led, technology enabled strategy within a given practice domain. Reporting line to the Region VP, Consulting and Analytics
Support sales and project delivery as a subject matter expert, driving delivery standardization through capabilities and IP assets across the Region. Work with GEO Directors to define project scope and provide input on proposals, contracts, and pricing
Serve as a player-coach, both individually contributing to project delivery in the practice and coaching other consultants
Monitor industry trends and develop standard messaging, sales decks, and marketing materials within a specific practice
Develop and grow a competitive, high-quality team of analytics consultants within specific practice domain, leading region-wide mentoring and talent and career development initiatives for the practice. Coordinate with the Global Development Centers to build off-shore / near shore headcount, skills, and capabilities to scale the business and be price-competitive
Contribute to the creation and execution of a go-to-market plan in line with the Global, Region, and geographical go to market strategy (special focus on the Analytics Consulting services needed to drive pull-through Teradata software revenue)
Drive and monitor consultant contributions to Business Value Frameworks within specific practice domain and drive repeatable offerings into Strategic Offering Management
Instill a culture of creating, capturing, and replicating IP within the practice in cooperation with the GEOs and Knowledge Management function and processes
Advise senior client leaders in the relevant practice domain
Develop strong working relationships with the Teradata Consulting team in order to create and manage integrated services offerings for customers
Bachelor’s Degree or Equivalent work experience
Eight years of experience running a practice within a consulting organization with analytics and business content
Extensive prior experience and ability to serve as a subject matter expert in one of the following areas: Industry Consulting, Business Consulting, Solutions, Analytics Delivery, Data Science, BI / Visualization, or Analytics Solution Development
Excellent people development and talent management skills, including the ability to support practice members as a player-coach
Ability to work cross-functionally in matrix organization where internal relationship building and credibility is critical
Prior leadership experience in the development of knowledge management and IP capture / re-use within a practice area, including special initiatives on field based development of new IP
Highly skilled in organizational politics, value proposition development, solution selling, focusing on the customer, sales ability / persuasiveness, and business needs analysis

Director Data Science Resume Examples & Samples

Leading a team of data scientists within ODC's R&D org
3+ years experience managing a team of data scientists
Expertise with a statistical analysis software package (R or Python)

Director, Data Science Resume Examples & Samples

Manage the development of predictive models to improve existing underwriting processes
Deliver on both quick-hit projects, which are typically shorter than 1 month, and long-term projects, which can span 12-24 months
Support technical modeling work as necessary
Establish project scope, timeline, and stage gates. Effectively communicate progress and blockers with stakeholders, tailoring communication to the appropriate level for various audiences
Collaborate with product teams, the business, and other stakeholders to incorporate feedback on underwriting processes
Manage up to 4 direct reports with strong technical backgrounds
Assist in setting overall GS Actuarial Analytics department strategy
Assist in growing the modeling team by recruiting top analytical talent
Direct the research of new statistical and mathematical techniques that are suitable and helpful for solving business related problems
Ph.D. in a quantitative discipline preferred
Knowledge of property/casualty industry as demonstrated by at least 8 years of relevant and progressively more challenging work experience
Demonstrated understanding of advanced techniques in statistics and predictive analytics. Expert analytic, quantitative and problem solving skills with proven ability to make data driven decisions and influence leaders
Strong business acumen and communication skills, as well as ability to effectively present technical concepts to non-technical individuals, including senior managers
Ability to foster and encourage teamwork and productive working relationships with stakeholders at all levels and across organizational lines; experience managing individuals or operations a plus

Senior Manager / Director Data Science Resume Examples & Samples

Manage partner relationship and delivery for one or more Fidelity business units (BU), working with BU stakeholders both in India and the US
Develop and nurture long term US partner relationships to achieve goals for the partner’s BU and for Data CoE
Engage with BU senior leadership to create strategy and long term data roadmaps
Evangelize Data CoE capabilities with business and technology stakeholders and identify engagement opportunities
Manage, mentor and develop associates
Build organizational capability in new data technologies
Deep knowledge and delivery experience in data technologies, including good experience in one or more of the following areas: Big Data, visualization&analytics, AI&Machine Learning
Very good awareness of industry trends in the above areas
Must be a forward thinking visionary leader who can help influence data strategy with partners
Ability to effectively work in ambiguous settings and matrixed organizational structures
Strong demonstrated ability to build effective teams, motivate and retain associates
Demonstrated track record in working with senior (VP level) stakeholders
Bachelors or Masters in Engineering. Computer Science preferred
Experience - 14+ years

Director, Data Science Resume Examples & Samples

Build and drive our analytic delivery strategy in partnership with business and technology leaders
Lead through influence and effectively champion the adoption of sophisticated analytic decision making systems throughout Allstate to significantly and demonstrably improve business results
Lead several agile product development teams in the data science space
Conceive, develop, implement and continually improve upon data science systems that integrate decision making across AORs and functions in support of Allstate strategies
Guide business leaders to understand and embrace the capabilities available to produce business outcomes as Allstate becomes an Integrated Digital Enterprise
Continually evaluate new analytic and big data techniques and technology for application and competitive advantage within the enterprise by staying current on new technology, analytics, and emerging trends in this and other industries; partner with Allstate technology to build and deliver new capabilities
Drive the development of additional capabilities to deliver business outcomes through the use of data and analytics within the analytic ecosystem Allstate is creating
Aggressively acquire and train new talent, maintaining a friendly and collaborative work environment, and develop future managers and leaders
10--12 years corporate experience
Transformational leadership to independently find opportunities to use analytics to improve results across the enterprise and collaborate across the organization to inspire change and capitalize on opportunities
The ability to develop and articulate a compelling vision and generate consensus and to influence across large organizations
A successful history of translating business objectives and problems into analytic problems, and analytic solutions into actionable business solutions
A proven ability to hire, develop, and effectively lead large teams of deeply technical resources
Extensive statistical and insurance domain knowledge including seasoned, in-depth, multi-dimensional knowledge of industry and company economics
Ability to concentrate on a wide range of loosely defined complex situations, which require application of creativity and originality, where guidance and counsel may be unavailable
High level organizational and product management skills in order to handle multiple concurrent assignments in a timely fashion

Senior Director, Data Science Resume Examples & Samples

15+ years building, managing, mentoring, and inspiring science teams, with a proven track record of leveraging data to drive significant business impact; quantitative methods should span statistical modeling, machine learning, optimization methods, econometrics, graph theories, artificial intelligence, text mining and NLP
Hands on experience in architecting data science solutions end to end from business initiatives to math formulation, algorithm selections, learning and validation, and optimization
Minimum 5 years in digital commerce, familiar with KPIs, A/B testing, and multivariate experimentation methods
Extensive experience with feature engineering, stable feature selections, unsupervised, supervised, and graph based learning algorithms - deep learning, reinforced learning and active learning, RNN, GAM, belief propagation, collaborative filtering, page rank, etc. for clustering, predictions, forecasting, and recommendations
Experience with ensemble technologies for a complex machine learning system with each sub-system performing a subset of learning and recommendations
Experience building and deploying machine learning, statistics, and/or optimization models in production
Solid statistical knowledge and intuition, ideally utilized in modeling and experimentation
Solid interpersonal and communication skills coupled with strong business acumen, along with the ability to influence peer organizations
Knowledge of retail and e-commerce customer domains highly desirable; Strong business acumen, and superior written, verbal and presentation skills
Able to deliver near-term wins while building towards a larger strategic vision
Proficient in data access methods for large customer and transactional databases; in developing high quality, reusable, and scalable service-based analytics supporting a wide variety of customer and business outcomes
12+ years of technical experience using quant tools – Julia, R, Python, SAS. Experience with AWS, Hadoop/Hive highly desirable. Knowledge of Kinesis/Kafka, Spark / Flink / Airflow, Scala, PMML, Tensor Flow Serving, KeyValue stores and Kubernetes is highly advantageous
Ph.D. in Statistics, Machine Learning, Mathematics, Operations Research, Engineering fields, Economics, or related quantitative field preferred

Director, Data Science Resume Examples & Samples

Manage and develop a team of up to four advanced analysts and actuarial students
Collaborate with CI Claims Strategy and Operations to develop business cases and specifications for predictive modeling products
Understand the competitive marketplace, IT environment, claims operations, and data challenges in order to deliver actionable insights, recommendations and business processes
Supervise and perform the construction, implementation and monitoring of predictive models
Provide tactical input on highly technically complex projects that drive change CI Claims
Present findings, share insights, and make recommendations that impact claims operations
Regularly engage with the data science and actuarial communities and lead cross-functional working groups, such as on improving the Data Science summer internship program
Competencies typically acquired through Master’s degree, Actuarial Designation or a minimum of 5 years of applied business/non-academic experience. 3 years of experience in Insurance or financial services industry experience preferred
Proven ability to learn advanced analytical techniques such as GLMs, advanced Reserving techniques or Capital Modeling
Proven ability to write and understand one or more programming languages, such as C++, Visual Basic, Python, R or SAS
Proven ability to manage projects and/or processes
Familiarity with the insurance industry and the departments which make up an insurer
Ability to give communicate effectively to management and other groups

Director, Data Science Resume Examples & Samples

3-5 years of direct line management
Experience with people process and technology
8 years’ experience in technology
Software as a product or service; Development, QA, Production, GTM
3-5 years’ experience in analytically based products
Exposure to data science and predictive solutions
Casualty and or auto physical damage
Claims process and decision points
Other P&C processes – pricing, reserving

TBA GEO Practice Director Data Science Resume Examples & Samples

Six years of experience running a practice within a consulting organization with analytics and business content
Extensive prior experience and ability to serve as a subject matter expert within the Data Science area
Strong understanding of market trends and technologies. This includes a solid understanding and experience using data with advanced analytics, business intelligence, data warehouse solutions, and big data analytics to improve business performance
Excellent customer executive and senior level relationship building capabilities
Experience in defining, launching, and executing successful initiatives on a topic or area of expertise
Master’s Degree

Director, Data Science, Customer Advocacy Resume Examples & Samples

Manage and develop a small team of advanced analysts and/or data scientists including selecting top talent, delivering continuous coaching, and providing rewards and recognition
Supervise and execute the creation, implementation and monitoring of analytic initiatives
Leverage vast quantities of structured and unstructured data to identify key drivers, improvement opportunities, emerging trends, etc
Develop models to predict customer experience attitudes and incorporate other analytics frameworks such as next best action
Present findings, share insights, and make recommendations to senior leadership of partner functions that impact the organization
Responsible for maintaining a body of knowledge on current and emerging technologies related to analytics, best practices and processes
Align day-to-day work with strategic customer-centric priorities, promote customer-centric principles, and support a customer-centric culture
Collaborate with broader analytics and data science community to share best practices in unstructured data analysis
Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and 2-4 years of relevant experience, a Master’s degree (scientific field of study) and 4-5 years of relevant experience or a Bachelor’s degree (scientific field of study) and 5-7 years of relevant experience
Deep proficiency with analytical software such as SAS, SQL, Python and R required
Knowledge of machine learning and data mining techniques strongly preferred
Strong analytical, problem solving, and organization skills
Strong oral and written communication skills required
Excellent collaboration skills and the ability to work within diverse organizations and teams
Ability to lead through influencing and working with people across multiple disciplines to achieve results
Knowledge of industry best practices and business operations

Senior Director Data Science Resume Examples & Samples

Establishing himself/herself as a strategic business partner with Brand VPGM’s and the Growth COE leadership team – clearly and concisely presenting findings and recommendations in a non-technical way to business leaders in multiple functions
Partnering with Brand, Marketing and Go-To-Market Insights to identify and define business issues requiring consumer targeting and advanced analytics as well as the resources needed to address them
Providing strategic direction to the company at multiple levels and maintaining focus on improving the effectiveness of Conagra’s investments and resources – translating strong analytical rigor into top and bottom line business impact
Leading a team of highly technical and accomplished Data Science managers and directors, determining their priorities and objectives, providing all necessary resources, driving a high standard of analytical quality, elevating the team’s expertise, and instilling in them business partnering and influencing skills
Ensuring Conagra continues to be a preferred partner for our vendors
Continuously raising the bar for Data Science capabilities and constantly looking to where Conagra needs to go analytically as a company – a data and analytics visionary
Bachelor’s degree required, Master’s degree preferred in a discipline heavily reliant on statistical or information theoretic methods
Proven track record of delivering actionable business recommendations, influencing decisions, and impacting results
Strong priority management skills to ensure analytical resources are leveraged and applied to the most important business issues
A history of turning insights into actions with brands, marketing, retailers, and consumers
Experience leading and developing teams of Data Science and analytics professionals
Demonstrated success driving a business model and influencing a matrix organization across brand, marketing, innovation, and R&D functions
Broad and deep knowledge of machine learning, deep learning, network/graph, A/B testing, NLP, transactional data, marketing measurement, visualization, and social media/listening methods
Experience working with large data sets (loyalty card, transaction, social media, etc.) and creating tools/solutions using that data
Experience working directly with large, cross-channel retailers and operators on driving their performance with shoppers and consumers
Proven effective oral and written communication skills – especially the ability to explain difficult concepts in simple, straightforward, business terms

Director Data Science Resume Examples & Samples

Bachelor’s Degree in Math, Computer Science, Statistics, or a related quantitative field
Expert command of statistical analysis, algorithm development, and state-of-the-art tools and methodologies for data science
8+ years creating predictive models using advanced machine learning techniques
3+ years managing a team of data scientists
Extensive experience working with data visualization and business intelligence tools such as Tableau
Experience working with cloud data warehouse technologies like AWS Redshift
Expert command of SQL and R or Python as applied to data science
Lead a team of 10+ data scientists in developing high-quality, robust predictive algorithms
Unify analytical resources from across the company into a cohesive team, develop a new process-driven service model, and ensure data solutions scale as MINDBODY grows
Create cross-training and tool sharing opportunities for analysts to foster career development, preparing the team to meet MINDBODY’s growing need for analytics and insights
Oversee both the Customer Intelligence and Business Intelligence groups
Work closely with the Chief Product Officer and other senior leaders to ensure Data Science initiatives align with MINDBODY strategic objectives
Work closely with the Sr. Director of Data Management and Sr. Director of Corporate Systems to develop and execute a comprehensive data strategy driving data governance best practices
Develop and manage a data roadmap including monetization strategies such as client-facing analytics and third-party data sharing opportunities
Oversee the development of analytical requirements to help drive data warehouse and corporate systems projects and initiatives
Champion the accelerated expansion and adoption of our data lake, as well as the use of automated and repeatable processes
Represent the voice of data analysts and promote data-driven decision making companywide
Identify opportunities throughout the organization to automate and improve processes
Work closely with IT/Sec, Legal, and legal to understand, monitor and propose changes to our data usage rights, privacy and security as outlined by our TOS, SLA and EULA
Work continually to identify new opportunities to provide valuable metrics to the business
Monitor, measure, and drive key performance indicators for Data Science as a service organization
Drive prioritization of highest ROI Data Science initiatives that maximize business value and actionable insights

Director, Data Science & Analytics Resume Examples & Samples

Job Specific
Bachelor’s degree, MBA or Master’s degree in quantitative studies. The equivalent combination of education, training and work experience may be suitable
Passion for digital analytics, working with data and deriving insights to answer client business questions
Experience leading and delivering marketing analytics engagements
Previous leadership experience and a proactive nature
Comfort with working in and contributing to a team based environment
Management and mentorship of junior employees
Understanding of client's business models and how SapientRazorfish can create custom solutions to support them

Director, Data Science Integration Resume Examples & Samples

Leads the development of a portfolio of data science products, projects, or initiatives directly in support of business operations and the integration of the Data Science Team through leveraging data mining, predictive analytics, and statistical analysis
Drive impactful change through the coordination of multiple work-streams of teams, both internal and external to the department, typically involving analytical projects and initiatives of a larger scale that involve complex data science concepts and resulting in significant, measurable transformation to operational processes
Deploy and develop technologies such as API's, software front-ends, and data visualizations to influence internal and external client teams to adopt, support, or integrate data science products, projects, or initiatives directly into operational systems and processes
Leverage analytical methodologies to develop business and functional requirements, schedules, and programmatic materials in support of data science products, projects, or initiatives
Regular, consistent, and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary
May have responsibility for developing and managing a budget
This position will involve up to 25% travel
Prior experience at a large consulting firm developing and deploying data-based solutions strongly preferred
Experience working with and leading quantitative/technical projects and professionals
Familiarity with the integration of data into operational processes through the use of RESTful API's and software applications
Experience leading multiple, complex work streams or projects with minimal supervision or oversight from management
Knowledge of SAS and other open source analytics tools such as R and Python
Knowledge of big data, including Hadoop (hiveQL)
Ability to grasp complex analytical principles and techniques
Proficiency in at least one analytical tool (e.g. SAS, R)

Senior Director, Data Science Resume Examples & Samples

Design a robust data architecture that integrates multiple disparate data feeds from a variety of sources with a focus on creating a holistic data store within an environment that supports accessible data mining, data analysis, and data science
Identify an adaptable, scalable big-data technology stack capable of accommodating multiple data feeds with requisite pre-processing, supporting necessary processing requirements for downstream consumption by various platforms, and fulfilling the analytics needs for a variety of data-driven initiatives
Collaborate with internal stakeholders across different divisions of SiriusXM to ensure that the data-driven strategy is designed with multiple business units' current and future intelligence and data needs in mind
Understand any existing data and technology resources and develop a strategic plan to close any gaps that are identified
Serve as Subject Matter and Domain Expert when translating business expectations and analytics needs into data and technology requirements and strategic analytics-based project plans
Provide leadership on data-driven endeavors that support the needs and objectives of the business in a variety of domains by promoting best practices that combine business analysis and rigorous supporting analytics
Manage expectations on work effort requirements and deliverable timeframes as dictated by technology and data related complexities
Continuously research cutting edge developments in data science, machine learning, and mathematical algorithmic design to creatively utilize new advances in big data for the purpose of extracting intelligence from SiriusXM's data
Champion data science methods when collaborating with the Strategic Analytics, Subscriber Analytics, and Marketing Analytics teams to harmonize data-supported intelligence efforts throughout different divisions of SiriusXM
Create a Data Science Center of Excellence to support SiriusXM's future data-driven initiatives within an ever-changing landscape of data driven capabilities, resources, and interests
1 Senior Data Scientist
3-5 Citizen Data Scientists
1 ETL Expert
Other technology personnel as dictated by the program
Graduate degree in a STEM field required
7-10 years of experience as a data scientist working with many different types of data
5-7 years of business analysis experience
5-7 years working with technology supporting large volumes of data processing in production environments
Experience building data architectures that support reporting, analysis, and processing needs
Experience as subject matter expert in multiple domains
Experience with system design, engineering, and architecture
Ability to pay attention to details and be organized
Ability to project a professional image over the phone and in person
Commitment to "internal client" and customer service principles
Ability to handle multiple tasks in a fast paced environment
Willingness to take initiative and to follow through on projects
Strong organizational skills and attention to details
Creative writing ability
Experience with data in a variety of formats (parquet, json, .wav files, relational, non-structured, etc.) and types (web and application traffic data, domain-specific metadata, customer data, transactional data, product data, etc.)
R, MatLab, C, Python, Perl, Scala or similar object-oriented programming languages
SQL, SSIS, Drill, SAS or other querying and ETL tools
Experience with big-data storage and processing tools like AWS, Oracle ExaDatabases, Hadoop, Drill, Spark
Visualization tools such as Tableau, Qlik, Adobe Analytics
·Thorough knowledge of MS-Office Suite (Word, Excel, PowerPoint, Access)

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Senior Director, Data Science Resume Examples & Samples

Director, Data Science Resume Examples & Samples

Director, Data Science Resume Examples & Samples

Senior Director Data Science Resume Examples & Samples

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Director, Data Science Resume Examples & Samples

Director, Data Science Resume Examples & Samples

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Director, Data Science Resume Examples & Samples

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Director, Data Science Resume Examples & Samples

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