Senior Data Scientist - Economist – Elasticity Modeling

CVS Health • Wellesley, MA

12d

About The Position

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 The Consumer Engagement & 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 products and insights. As a member of the Pricing Analytics team, you will be at the forefront of delivering high visibility products for key CVS Retail strategic priorities. Specifically, you will have the opportunity to drive traffic, revenue and customer satisfaction in CVS Health’s Front Store business using data science to optimize pricing decisions. In this role, you will have the opportunity to: Solve complex problems, translate business requirements into testable hypotheses and measurable metrics, build causal, causal ML, and/or predictive models to understand localized trends, assess the competitive environment, and measure short- and long- term customer impacts to optimize pricing 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 and metrics 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 the pricing models, rethink the deployment readiness and scalability of the models, and automation opportunities using agents, 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, 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

• Bachelor’s degree in a quantitative field such as economics, statistics, or a related field. Master’s degree is preferred.
• 3+ years of work experience in retail, consulting, or a related field
• Demonstrated experience applying statistical models and/or causal inference techniques (such as Hierarchical GLM, Double ML, synthetic control, and other quasi experimental techniques). Familiarity with surrogate models.
• Strong Python, R, and SQL skills, proficiency in working with large datasets
• 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.

Nice To Haves

• PhD in economics or equivalent
• 5+ years of work experience in retail, consulting, or a related field
• Experience developing elasticity models, in depth understanding of merchandising (price, promotion, assortment) concepts and metrics in retail
• Experience with managing large scale projects and working with multiple business stakeholders.

Responsibilities

• Solve complex problems, translate business requirements into testable hypotheses and measurable metrics, build causal, causal ML, and/or predictive models to understand localized trends, assess the competitive environment, and measure short- and long- term customer impacts to optimize pricing 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 and metrics 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 the pricing models, rethink the deployment readiness and scalability of the models, and automation opportunities using agents
• 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

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level