Lead Data Scientist - Forecasting

Position Summary
The Forecasting Center of Excellence (COE) at CVS Health builds scalable forecasting systems that support pricing, promotions, and assortment decisions across the retail business. As a Lead Data Scientist, you will own how demand is modeled and used for decision‑making, rather than simply predicting it. This role focuses on defining and scaling a unified forecasting framework that produces consistent outputs across use cases, working with data science, engineering, product management, software development, and business teams to ensure forecasts are accurate, stable, and usable in real decision workflows.

Responsibilities

Own the design and evolution of a unified forecasting architecture, defining how demand is constructed.

Integrate internal and external data sources (e.g., coupon redemption, merchandising, competitive, macroeconomic) into scalable forecasting pipelines.

Evaluate tradeoffs across forecasting methods and ensure outputs are stable, interpretable, and decision‑ready.

Develop scenario planning and simulation frameworks to measure the business impact of pricing, promotions, and assortment decisions.

Implement robust MLOps practices for deployment, monitoring, and retraining in cloud environments (Azure, GCP, AWS).

Elevate the technical bar of the organization by establishing a culture of continuous learning and championing the recruitment of top‑tier analytical talent.

Lead the exploration of state‑of‑the‑art machine learning and deep learning techniques.

Translate complex business objectives into a multi‑quarter data science roadmap, prioritizing high‑impact initiatives from research through deployment, while managing technical debt and ensuring alignment with cross‑functional product milestones.

Qualifications

Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field (PhD preferred).

Seven or more years of experience in forecasting or demand modeling, ideally in a retail or B2C environment, including hands‑on deployment of enterprise‑level production forecasting systems with measurable impact.

Three or more years 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.).

Four or more years of experience with Python and SQL for large‑scale data processing.

Excellent communication, leadership, and presentation skills with attention to detail; agile experience and flexibility to adapt to changing business needs.

Proven experience leading multiple complex projects simultaneously in a fast‑paced environment.

Experience mentoring junior team members and setting standards for forecasting approaches, model validation, and code quality.

Preferred Qualifications

Experience applying demand forecasting methods in a retail environment.

In‑depth understanding of merchandising concepts and metrics.

Experience managing large‑scale projects and working with multiple stakeholders in a matrixed environment.

Education

Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field.

Advanced degree (PhD) preferred in quantitative disciplines with applied forecasting experience.

Pay Range
The typical pay range for this role is: $130,295.00 – $260,590.00. This 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 factors such as experience, education, geography, and other relevant considerations. The position is eligible for a CVS Health bonus, commission or short‑term incentive program in addition to the base pay range, and also includes an award target in the company's equity award program.

Benefits
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. Benefits include medical, dental, and vision coverage; paid time off; retirement savings options; wellness programs; and other resources, based on eligibility. Additional details about available benefits are provided during the application process.

Application Deadline
05/31/2026.

EEO Statement
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

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