Data Scientist - Retail Demand Sensing

What the role needs

• Develop and maintain machine learning models that forecast product demand at multiple levels of aggregation (SKU, store, category, and distribution center).
• Enhance demand sensing capabilities using internal and external signals, including promotions, pricing, weather, seasonal events, demographics, competitor activity, and market trends.
• Evaluate forecasting performance using appropriate accuracy metrics and continuously improve model effectiveness.
• Conduct root-cause analysis of forecast misses and recommend corrective actions.
• 1 years of experience in data science, machine learning, forecasting, or advanced analytics.
• Experience developing predictive or forecasting models in a business environment.
• Experience working with large-scale structured datasets.
• Python, SQL, and data manipulation frameworks.
• Time-series forecasting techniques (ARIMA, Prophet, gradient boosting, machine learning forecasting methods).
• Machine learning model development and validation.
• Feature engineering and statistical analysis.
• Data visualization tools such as Power BI, Tableau, or similar platforms.

From the employer

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 Data Scientist - Demand Sensing is responsible for developing, enhancing, and operationalizing machine learning forecasting solutions that improve demand visibility and inventory decisions across the business. This role focuses on translating complex demand signals into actionable forecasts by leveraging internal and external data sources, advanced statistical techniques, and machine learning models. The position partners closely with Inventory Planning, Supply Chain, and Technology teams to improve forecast accuracy, reduce working capital, improve on-shelf availability, and support replenishment decision-making through scalable analytics products. This role owns discrete forecasting initiatives and contributes to broader demand sensing product roadmaps. Develop and maintain machine learning models that forecast product demand at multiple levels of aggregation (SKU, store, category, and distribution center). Enhance demand sensing capabilities using internal and external signals, including promotions, pricing, weather, seasonal events, demographics, competitor activity, and market trends. Evaluate forecasting performance using appropriate accuracy metrics and continuously improve model effectiveness. Conduct root-cause analysis of forecast misses and recommend corrective actions. Required Qualifications 1 years of experience in data science, machine learning, forecasting, or advanced analytics. Experience developing predictive or forecasting models in a business environment. Experience working with large-scale structured datasets. Python, SQL, and data manipulation frameworks. Time-series forecasting techniques (ARIMA, Prophet, gradient boosting, machine learning forecasting methods). Machine learning model development and validation. Feature engineering and statistical analysis. Data visualization tools such as Power BI, Tableau, or similar platforms. Cloud-based analytics environments and version control practices. Preferred Qualifications Retail, supply chain, inventory planning, replenishment, or merchandising analytics. Demand forecasting and demand sensing applications. Experience leveraging external demand drivers such as weather, events, seasonality, and pricing signals. Education Bachelor s degree in Data Science, Statistics, Mathematics, Computer Science, Operations Research, Economics, Engineering, or related field. Master s degree preferred. Anticipated Weekly Hours 40 Time Type Full time Pay Range The typical pay range for this role is: $86,520.00 - $173,040.00 This 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 people We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. 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. The benefits for this position 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 and on Benefits Moments . We anticipate the application window for this opening will close on: 11/22/2026 Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.