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 Consumer Engagement & Analytics team partners with key functions across CVS Health to improve the customer experience through impactful analytics and modeling. As part of the Forecasting Center of Excellence, you will help develop high-visibility products tied to core CVS Retail strategies. This role focuses on building scalable forecasting solutions that drive smarter pricing, promotional, and assortment decisions across the Front Store (non-pharmacy retail).
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As a member of this team, you will work on solving complex forecasting problems, simulating business decisions, and applying cutting-edge ML and AI techniques to improve forecast accuracy, speed, and operational impact. You will collaborate cross-functionally to embed these models into business workflows and planning tools.
If you are passionate about using data to drive real-world decisions and excited by the challenge of forecasting at scale across thousands of products and locations - this role is a great fit.
Key responsibilities
- Solve complex forecasting problems by translating business needs into data science use cases and testable hypotheses
- Leverage large datasets, optimize code, and build scalable and deployment ready models that work well with CVS Retail's diverse product portfolio
- Build and scale statistical, machine learning, and deep learning forecasting models that work across product maturity stages (e.g., seasonal, new, declining)
- Simulate the impact of business decisions - such as price changes, promotions - to help improve customer experience and operational outcomes
- Develop a deep understanding of merchandising and retail planning workflows; connect modeling efforts to actionable business outcomes
- Utilize the latest developments in generative AI (e.g., LLMs and foundation models) to improve forecast model performance, feature enrichment, and automation opportunities
- Develop robust methodologies and key forecasting performance metrics such as accuracy, bias, and stability over time
- Work with ML Ops teams to deploy and maintain production-ready pipelines using cloud platforms such as Azure, GCP, or Databricks
- Collaborate cross-functionally with engineering, platform, pricing, promotions, assortment and category teams to embed models into production workflows and decision-making tools
- Present analytical findings and scenario outcomes clearly to variety of audiences including internal stakeholders and senior leadership
- Help raise modeling standards across the team by sharing reusable tools, best practices, and informal mentorship
- Stay up to date on the state-of-the-art modeling methodologies and latest research
- Experience with ARIMA, exponential smoothing, Prophet, gradient boosting, LSTM, or hybrid ensemble models
- Forecasting across hierarchies (e.g., SKU, category, store) and managing temporal aggregation
- Strong programming skills in Python or R, and proficiency with SQL and large-scale data processing
- Hands-on experience working with ML Ops tools, version control (GitLab or GitHub), ML platforms (SageMaker, Vertex AI, Databricks), and containerization (Docker, Kubernetes)
- Demonstrated ability to present insights and technical concepts to both business and technical audiences
- Strong communication skills with the ability to present insights and technical findings to both technical and business stakeholders
- Adaptability to fast-changing environments, comfortable working in Agile teams, and able to balance technical depth with speed to delivery.
- 3+ years of relevant experience in forecasting, planning analytics, or merchandising optimization
- Experience forecasting in retail settings and understanding how forecasts are consumed by merchandising and planning teams
- Familiarity with feature engineering for forecasting using pricing, promotion, and assortment data and simulation frameworks to support scenario planning and what-if analysis
- Strong understanding of time-based trends, demand patterns, and how they inform pricing, promotional, and supply chain decisions
- Experience applying generative AI (e.g., embeddings, LLMs) to feature engineering or forecasting enhancement
- Exposure to end-to-end model lifecycle management, including versioning, retraining, and monitoring for data drift
- Experience managing large-scale projects and working with multiple business stakeholders
- Bachelor's degree in a quantitative field such as Statistics, Mathematics, Engineering, Computer Science, or Economics
- Master's preferred.
40Time Type
Full timePay Range
The typical pay range for this role is:$79,310.00 - $173,040.00This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.Great benefits for great peopleWe take pride in our comprehensive and competitive mix of pay and benefits - investing in the physical, emotional and financial wellness of our colleagues and their families to help them be the healthiest they can be. In addition to our competitive wages, our great benefits include:
- 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.