Senior Data Scientist - Assortment

 Position Description

• 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.  

In this role, you will have the opportunity to:

• Solve complex problems, translate business requirements into testable hypotheses and, build predictive models to understand localized trends,
• 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 and metrics to assess model performance,
• Stay up to date on the state-of-the-art modeling methodologies and latest research, foster a culture of continuous learning,
• Coach and mentor junior data scientists, providing guidance on best practices, technical skill development, and project execution, lead knowledge-sharing sessions and code reviews to elevate the team’s expertise,
• Work cross functionally with a range of technical and non-technical stakeholders including business partners, engineers, product managers, 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,

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.

Required Qualifications 

• Bachelor’s degree in a quantitative field such as engineering, computer science, statistics, or a related field. Master’s degree is preferred.
• 3+ years of work experience in retail, consulting, or a related field, in an applied data science role.
• Demonstrated experience analyzing large, complex datasets and applying statistical and/or ML models (such as clustering, segmentation, predictive models) to identify trends, patterns, and relationships, segment data, and support business strategies.
• Apply text analysis methods to extract insights from unstructured data.
• Strong Python and SQL skills,
• 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.),
• Excellent communication and presentation skills and attention to detail. Worked in an agile environment, has the flexibility to adapt to changing business needs.

Preferred Qualifications 

• Advanced degree (PhD) in engineering, computer science, statistics, applied mathematics or a related field,
• 5+ years of work experience in retail, consulting, or a related field,
• In depth understanding of merchandising (price, promotion, assortment) concepts and metrics in retail,
• Ability to manage multiple projects and prioritize tasks in a fast-paced environment,  
• Experience with managing large scale projects and working with multiple business stakeholders.