About the role
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary We are seeking a skilled and analytical Senior Product Analyst to lead the development and execution of a data-driven product roadmap. The ideal candidate will have a deep understanding of product analytics, strong problem-solving skills, and experience working with cross-functional teams to support strategic initiatives. As a Senior Product Analytics Associate, you will work closely with cross-functional teams including engineering, product, and clinical operations. Roles and
Responsibilities: Define, track, and report on product metrics including performance and profitability Build and maintain robust data transformation models using dbt (or similar frameworks like Dataform or SQL-based ETL tools) to ensure analytics-ready datasets Build and maintain Power BI dashboards to track product health and monitor the success of product initiatives Design and interpret A/B tests; when A/B testing is not feasible, apply causal inference methods (e.g., Diff-in-Diff, Propensity Score Matching) to determine product efficacy. Develop ROI projections for analytics projects to prioritize deliverables by business impact Tell compelling stories through data, articulating technical information to a non-technical audience Basic
Qualifications: Bachelor’s degree in a technical field (Statistics, Data Science, CS, Engineering, or related) 5+ years of experience in a technical product analytics or data science role Experience with dbt (Data Build Tool) or similar analytics engineering tools, including version control (Git) Experience with A/B testing, funnel analysis, and statistical methods (regression, clustering, or predictive modeling). Advanced proficiency in SQL and experience with Python or R Experience working with data engineering teams to develop data pipelines Preferred
