Senior Data Scientist - Assortment Optimization

CVS Health•Wellesley, MA

About The Position

At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care. As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day. Position Summary The Consumer Engagement & Analytics team is helping lead the effort to drive improved customer experience and operational efficiency through data-driven decision making. As a member of the Assortment Optimization team, you will be at the forefront of designing and deploying large-scale optimization and AI-driven analytics that shape how CVS determines the right mix of products across thousands of stores and millions of customers. Specifically, you will have the opportunity to work on a problem of massive scale and complexity focused on balancing business goals, customer preferences, and operational constraints across one of the largest retail networks in the world. In this role, you will have the opportunity to: Solve complex optimization problems using operations research, dynamic programming, and reinforcement learning to guide SKU-level assortment and product placement decisions. Develop scalable models that quantify trade-offs between customer demand, profitability, inventory risk, and product diversity, translating real-world business logic into mathematical frameworks. Stay up to date on state-of-the-art modeling methodologies and research, and apply them to improve the scalability, robustness, and interpretability of assortment models. Leverage the latest developments in generative AI and other AI models to enrich forecasting, simulation, and decision-support capabilities. Collaborate cross-functionally with merchandising, pricing, supply chain, and data engineering teams to ensure analytics solutions are actionable and deployable at enterprise scale. Communicate insights effectively to technical and non-technical stakeholders, influencing strategic planning and execution with data-driven recommendations. We are a fast-paced team focused on building innovative advanced analytics solutions using cloud capabilities. Within our team, we believe cutting-edge AI products and analytics can only be delivered if every aspect of the solution from data to model to front end UI is fully designed and developed by the team. We are looking for talented individuals who have a strong sense of ownership, accountability and a desire to deliver high quality end to end intuitive and impactful analytic products using advanced data driven approaches.

Requirements

3+ years of work experience applying optimization or mathematical modeling to real-world business problems — ideally in retail, supply chain, pricing, or assortment
Demonstrated experience applying operations research, reinforcement learning, and/or dynamic programming techniques
Experience working with a data engineering/MLOps team to productionize data science models, familiarity with version control (GitLab or GitHub), and ML platforms (AWS SageMaker, Databricks, GCP Vertex AI, etc.)
Strong Python, and SQL skills, proficiency in working with large datasets, and experience using optimization frameworks such as Gurobi, Pulp, Pyomo, or OR-Tools
Familiarity with machine learning or simulation techniques (forecasting, clustering, demand modeling) that complement optimization
Ability to translate complex business constraints into mathematical formulations and develop scalable, production-ready solutions
Strong communication and storytelling skills; able to distill quantitative insights into clear, actionable recommendations for non-technical audiences.

Nice To Haves

5+ years of work experience in retail, consulting, or a related field
Experience developing price optimization models, in depth understanding of merchandising (price, promotion, assortment) concepts and metrics in retail
Understanding of reinforcement learning, simulation-based optimization, or generative AI applications in decision systems
Exposure to MLOps and data engineering tools (Databricks, Vertex AI, AWS SageMaker, Airflow, etc.) for end-to-end model deployment
Demonstrated ability to balance theoretical rigor and practical constraints — developing models that are both explainable and operationally viable
Experience with managing large scale projects and working with multiple business stakeholders.

Responsibilities

Solve complex optimization problems using operations research, dynamic programming, and reinforcement learning to guide SKU-level assortment and product placement decisions.
Develop scalable models that quantify trade-offs between customer demand, profitability, inventory risk, and product diversity, translating real-world business logic into mathematical frameworks.
Stay up to date on state-of-the-art modeling methodologies and research, and apply them to improve the scalability, robustness, and interpretability of assortment models.
Leverage the latest developments in generative AI and other AI models to enrich forecasting, simulation, and decision-support capabilities.
Collaborate cross-functionally with merchandising, pricing, supply chain, and data engineering teams to ensure analytics solutions are actionable and deployable at enterprise scale.
Communicate insights effectively to technical and non-technical stakeholders, influencing strategic planning and execution with data-driven recommendations.

Benefits

Affordable medical plan options, a 401(k) plan (including matching company contributions), and an employee stock purchase plan.
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching.
Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.

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