Lead Data Scientist - Retail Strategic Health Analytics

CVS Health•New York, NY

About The Position

The Lead Data Scientist will play a critical role in developing, scaling, and deploying best-in-class forecasting models that drive merchandising category forecasting and decision-making. This role sits within a high-impact data science team responsible for translating complex transactional and behavioral data into accurate, actionable forecasts that inform financial, labor, and promotional strategies. The Lead Data Scientist will own end-to-end model development, from problem formulation and feature engineering through validation, deployment, and ongoing performance monitoring, while providing technical leadership and mentorship to other data scientists.

Requirements

7+ years of professional experience in data science, applied statistics, or machine learning
Hands-on experience developing time series forecasting or predictive models in a production environment
Proficiency in Python for data analysis and model development
Experience working with SQL and large, structured datasets
Demonstrated experience applying statistical or machine learning techniques (e.g., regression, tree-based models, time series models)
Experience deploying, maintaining, or operationalizing models in partnership with engineering or analytics teams
Previous experience in a lead or senior individual contributor role, owning model design and technical decisions
Bachelor’s degree or equivalent work experience in Mathematics, Statistics, Computer Science, Analytics, Engineering, or a related discipline

Nice To Haves

Strong problem-solving skills with the ability to translate ambiguous business questions into well-defined analytical problems
Experience influencing stakeholders and communicating model insights to non-technical audiences
Background in finance, retail, or demand forecasting domains
Experience mentoring junior data scientists or providing technical leadership across projects
Familiarity with model monitoring, performance drift, and iterative model improvement
Ability to balance statistical rigor with pragmatic business constraints and timelines
Master’s degree preferred

Responsibilities

Develop, scale, and deploy best-in-class forecasting models that drive merchandising category forecasting and decision-making
Translate complex transactional and behavioral data into accurate, actionable forecasts that inform financial, labor, and promotional strategies
Own end-to-end model development, from problem formulation and feature engineering through validation, deployment, and ongoing performance monitoring
Provide technical leadership and mentorship to other data scientists