Data Scientist - CVS Media Exchange

CVS Health-posted 11 months ago
$86,520 - $173,040/Yr
Full-time • Entry Level
Hybrid • New York, NY
5,001-10,000 employees
Health and Personal Care Retailers
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Join the Consumer Engagement Analytics (CEA) team for an opportunity to leverage advanced analytics, experimentation, causal inference, and strategic problem solving to grow digitally enabled products at CVS Health. CVS Media Exchange [CMX] is dedicated to driving measurable outcomes for our suppliers, merchants, stores, GMs, brand advertisers, and agencies. Our full-funnel ad solutions leverage CVS's in-store and online data, extensive reach, and to provide measurable results for our clientele. With a range of flexible pricing and buying models, including self-service; these solutions help businesses build brand awareness, engage with CVS consumers, and convert CVS consumers to shoppers. As a team supporting enterprise products (CVS Media Exchange, and CVS.com / mobile app), you'll be exposed to all the business units within CVS Health.

  • Understand business problems and translate them to analytics solutions.
  • Analyze customer journeys to identify opportunities to drive more adoption, engagement, retention, and conversion.
  • Develop personalization capabilities using machine learning to target specific audiences for relevant outreach.
  • Design online experiments (AB testing), measure, and optimize.
  • Leverage techniques like causal inference and MMM to supplement experiments where AB testing is not possible or appropriate.
  • Develop and/or use algorithms and statistical predictive models and determine analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes.
  • Perform analyses of structured and unstructured data to solve multiple and/or complex business problems utilizing advanced statistical techniques and mathematical analyses.
  • Collaborate with business partners to understand their problems and goals, develop predictive modeling, statistical analysis, data reports, and performance metrics.
  • Develop and participate in presentations and consultations on analytics results and solutions.
  • Interact with internal and external peers and managers to exchange complex information related to areas of specialization.
  • Use strong knowledge in algorithms and predictive models to investigate problems, detect patterns, and recommend solutions.
  • Use strong programming skills to explore, examine, and interpret large volumes of data.
  • 1+ years of experience applying modern machine learning techniques to build predictive models for both classification and regression problems.
  • 1+ years of experience utilizing Python and SQL.
  • Experience extracting actionable insights from the analysis and interpreting outcomes of complex models to present to business audiences including technical, non-technical, and senior leaders.
  • Experience preparing data for analysis, working with data engineering team to create modeling dataset, assess completeness and quality of data, and perform feature engineering.
  • Experience applying knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources.
  • Experience with experimental design and supervised/unsupervised machine learning approaches.
  • Experience designing online experiments (AB testing) a plus.
  • Demonstrates strong ability to communicate technical concepts and implications to business partners.
  • Ability to communicate effectively and confidently with business partners, project team members, and senior management.
  • Ability to anticipate and prevent problems and roadblocks before they occur.
  • Demonstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, experiment design, and predictive modeling and in-depth specialization in some areas.
  • Full range of medical, dental, and vision benefits.
  • 401(k) retirement savings plan.
  • Employee Stock Purchase Plan available for eligible employees.
  • Fully-paid term life insurance plan for eligible employees.
  • Short-term and long-term disability benefits.
  • Numerous well-being programs.
  • Education assistance and free development courses.
  • CVS store discount and discount programs with participating partners.
  • Paid Time Off (PTO) or vacation pay, as well as paid holidays throughout the calendar year.
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