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# Data Scientist - Retail Demand Sensing

- **Company:** CVS Health
- **Location:** New York, NY, United States (Remote available)
- **Salary:** $86,520 - $173,040
- **Contract:** Permanent contract
- **Skills:** Cloud Computing, Data Visualization, Python (Programming Language), Machine Learning, Power BI, SQL Databases, Tableau (Software), Data Processing, Feature Engineering, Prophet, Information Technology, Xgboost, Software Version Control
- **Published:** October 23, 2026
- **Apply:** https://dejobs.org/x/x/0C090308622E4AA98302F15B066FE968/job/

## About the Role

* 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.

## Description

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.