Senior Product Manager - Foundational and Clinical AI
Listed on 2026-03-05
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IT/Tech
AI Engineer, Data Analyst, Data Science Manager, Machine Learning/ ML Engineer
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.
PositionSummary
CVS Health’s Analytics & Behavior Change (A&BC) is an organization working to solve some of the most challenging problems at the intersection of technology and healthcare. A&BC leverages advanced analytics, machine learning, modeling, and hypothesis‑driven approaches to transform data into actionable, customer‑centric insights driving growth, health outcome improvements, and access to health care across all our businesses in CVS Health. Our teams build next generation data and machine learning platforms and software products that help power CVS Health to make healthier happen for 100+ million customers.
A&BCClinical Data Science & AI Product Team
The A&BC organization is looking to grow its Product team supporting Clinical Data Science & AI. Join us as we embark on an exciting journey to drive a transformational shift in how CVS Health leverages technology and analytics to become the leader in consumer healthcare in the U.S.
Senior Product Manager RoleAs a Senior Product Manager within A&BC, you will be responsible for contributing to the creation, launch, and maintenance of AI‑powered, clinical data insights across the enterprise. This role requires a strong understanding of product management, clinical data, AI‑powered insights acceleration, and cross‑team collaboration. The ideal candidate has familiarity with the following areas: development processes of small language models, natural language processing, training models, data annotation, and model validation.
This person can work effectively with cross‑functional teams, most importantly data scientists and machine learning engineers, to bring clinical data and AI products from inception to production.
- Develop feature KPIs that are aligned with the overall program KPIs and ensure metrics tracking; use data to drive feature prioritization and alignment with stakeholders on value and prioritization.
- Work closely with clinicians and operations to confirm business value, inform problem statements, and quantify the value of your team’s potential solution.
- Develop go‑live timelines with your core data science team and engineering partners; align on timelines and scope with multiple developer teams and stakeholders.
- Facilitate cross‑team hand‑offs including documentation, end‑to‑end QA planning, and validation.
- Create product requirements documents, acceptance criteria, and detailed product specifications to communicate feature requirements to Data Science, Engineering, and Leadership teams.
- Support Engineering and Data Science teams to implement features by clarifying requirements, facilitating technical discussions, and helping technical team members to understand the end users and the business problem being solved. Ensure end‑to‑end insight and collaboration.
- Facilitate problem solving and prioritization across teams, factoring in trade‑offs between speed, scalability, accuracy, and quality. Be prepared to discuss myriad AI solutions during discovery and make trade‑off decisions.
- Liaise with clinicians to validate clinical AI model results and to facilitate review and refinement.
- Analyze product performance metrics, identifying opportunities for improvement and optimization.
- Work with internal customers, end users, and other stakeholders to maintain product roadmaps.
- Clarify and coordinate dependencies with other product teams and stakeholders and mitigate the risks and dependencies proactively.
- Follow agile best practices including but not limited to working with and leading a scrum team.
- 8+ years of overall work experience.
- 3+ years’ experience working cross‑functionally with Machine Learning Engineering and Data Science.
- 2+ years’ Product Management, Product…
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