Data Scientist - Assortment Optimization, CVS Health

CVS Health

Location:
United States, Wellesley, Massachusetts

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

86520.00 - 173040.00 USD / Year

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Job Description:

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. The Retail Analytics team is helping lead the effort to drive improved consumer experience by partnering with key business areas across CVS Health to deliver impactful analytic solutions and insights. As a member of the Analytics & Behavior Change (A&BC) Merchandising Analytics team, you will be at the forefront of delivering high visibility projects for key strategic priorities. Specifically, you will have the opportunity to drive revenue and customer satisfaction in CVS Health’s Front Store business by using data science to support a product assortment that better fits the needs of our customers.

Job Responsibility:

Solve complex problems using operations research, dynamic programming, and reinforcement learning, build and improve optimization models to optimize assortment decisions
Develop and leverage in-depth knowledge of Retail Merchandising business processes, translate key drivers of business value to analytics opportunities, and simulate impact of business decisions to improve customer experience
Guide the technical approach, leverage large datasets, and build scalable and deployment ready models that work well with CVS Retail’s diverse product portfolio, develop robust methodologies to assess model performance
Stay up to date on the state-of-the-art modeling methodologies and latest research
Utilize the latest developments in the generative models (LLMs and other AI models) to improve and enrich the performance of current models
Work cross functionally with a range of technical and non-technical stakeholders including business partners, engineers, and other data and analytics teams. Share progress, findings, recommendations, and their business implications. Present meaningful and insights-driven materials on analytical results with recommendations and go forward planning to guide a variety of audiences including internal stakeholders and senior leadership

Requirements:

Bachelor’s degree in a quantitative field such as Operations Research/Industrial Engineering, Applied Mathematics, Computer Science, Engineering, or a related field
Strong Python and SQL skills, proficiency in working with large datasets
Familiarity with mathematical optimization models using open-source or commercial optimization solvers (such as Pyomo, Gurobi, Pulp, ILOG CPLEX)
Experience working with a data engineering/MLOps team to deploy data science models, familiarity with version control (GitLab or GitHub), and ML platforms (AWS SageMaker, Databricks, GCP Vertex AI, etc.)
Excellent communication and presentation skills and attention to detail. Worked in an agile environment, has the flexibility to adapt to changing business needs
Ability to communicate technical concepts to non-technical audiences, including experience creating communication materials (e.g., white paper, slide decks, etc.)

Nice to have:

Master’s degree in a quantitative field
2+ years of work experience in retail, consulting, or a related field
Experience solving pricing, promotions, assortment, or supply chain problems
Experience developing price optimization models, in depth understanding of merchandising (price, promotion, assortment) concepts and metrics in retail
Experience managing large scale projects and working with multiple business stakeholders

What we offer:

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

Additional Information:

Job Posted:
July 20, 2025

Expiration:
August 31, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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Data Scientist - Assortment Optimization