Data Scientist – Forecasting

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).

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

Required qualifications

1+ years of experience in time series forecasting, demand planning, or applied predictive modeling, including:

• 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.

Preferred Qualifications

• 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 th