Lead Data Scientist (Medicare Sales Strategy)

CVS Health•Hartford, CT

6d•$130,295 - $260,590

About The Position

CVS Health is seeking a Lead Data Scientist to own the analytical strategy and data science roadmap for its Medicare sales organization and advocate for AI adoption across the Sales Center of Excellence (SCOE). The role sets technical direction, leads a team of data scientists and analysts, and partners with sales leadership on data-driven and AI-enabled growth initiatives across Medicare Advantage and Part D markets. The Lead Data Scientist defines the strategy for data science and AI supporting Medicare sales, distribution, and enrollment growth; oversees modeling pipelines and the sales data ecosystem; and establishes standards for model development, validation, deployment, and monitoring. The role translates business questions into analytical programs, communicates recommendations to senior leaders, and works with Engineering and IT to put models and insights into sales workflows. The position requires a bachelor's degree or equivalent experience. A master's or PhD in a related field, or equivalent experience, is preferred. The stated annual base salary range is $130,295 to $260,590. The role is also eligible for a CVS Health bonus, commission or short-term incentive program and an award target in the company's equity award program. The full-time position is eligible for benefits including medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. The application window is anticipated to close on 11/30/2026.

Requirements

At least 5 years in data science or advanced analytics, including at least 3 years in a lead, staff, or principal capacity.
At least 1 year supporting Medicare, Medicare Advantage, or Part D sales or distribution organizations.
Proven experience leading and mentoring a team of data scientists or analysts.
Demonstrated experience advocating for and driving AI or advanced analytics adoption within a business unit or center of excellence.
Expert-level SQL skills.
Advanced proficiency in Python or R for modeling, automation, and pipeline development.
Deep experience with CMS data assets, including enrollment files, landscape files, and MCMG-regulated data.
Experience integrating CRM platforms such as Salesforce or similar, broker/FMO data, and BI platforms such as Power BI, Tableau, or Looker.
Strong communication skills, including the ability to explain complex models and AI concepts in executive-level narratives.
Bachelor's degree or equivalent experience.

Nice To Haves

At least 8 years of experience in data science or advanced analytics and at least 3 years on a Medicare-related team.
Experience with MLOps practices, including model versioning, monitoring, drift detection, and retraining workflows.
Hands-on experience with generative AI, LLM integration, or AI product development in an enterprise setting.
Background in territory optimization, GIS analysis, or market sizing for Medicare-eligible populations.
Master's or PhD in Statistics, Data Science, Computer Science, or a related field, or equivalent experience.

Responsibilities

Define and drive data science and AI strategy supporting Medicare sales, distribution, and enrollment growth.
Champion AI adoption across SCOE by identifying high-value use cases, building investment cases, and guiding teams in adopting AI-powered tools and workflows.
Lead, prioritize, review the work of, and develop a team of data scientists and analysts.
Architect and oversee end-to-end modeling pipelines for lead scoring, enrollment forecasting, agent performance, and retention risk.
Own the sales data ecosystem, including governance, quality standards, and integration across CRM, CMS, and internal platforms.
Translate ambiguous questions from Sales, Marketing, and Finance leadership into structured analytical programs.
Establish team best practices for model development, validation, deployment, and monitoring, including generative AI and LLM-based applications.
Present findings and recommendations to VP- and C-suite stakeholders and influence strategic decisions with data.
Partner with Engineering and IT to productionize models and embed insights into sales workflows and tools.
Represent the data science and AI function in cross-functional planning, budgeting, and roadmap discussions.