Senior Manager, Data Partnerships & Monetization

Client: CVS Health — Analytics & Behavior Change (A&BC) | New York, NY / Hybrid Engagement type: Contract-to-hire. Initial contractor engagement with planned conversion to full-time employment pending performance and mutual fit.

Partnership Development & Deal Execution

• Identify, source, and develop new data partnership and commercialization opportunities across healthcare, life sciences, technology, and adjacent industries
• Build and manage a pipeline of strategic partnerships, engaging prospective partners and advancing opportunities from initial discussions through deal execution
• Represent CVS Health in external forums, conferences, and partner meetings to expand market presence and originate new opportunities
• Partner with the VP of Data Products and Monetization to shape and advance new partnership opportunities, including developing commercial materials, defining partnership structures, and supporting external discussions
• Develop and standardize repeatable partnership models, including how partnerships are structured, governed, and operated, to enable scalable growth

Partner Ownership and Execution

• Own the end-to-end operational health of active data licensing partnerships including tracking deliverables, schema changes, feed updates, and SLA compliance
• Maintain clear, up-to-date documentation of data product specifications, schema changes, and release notes, ensuring partners have accurate technical reference material
• Coordinate with Data Engineering teams and partner teams to scope and deliver product enhancements (e.g., frequency upgrades, schema expansions), translating technical requirements into partner-ready solutions
• Track and report on revenue across internal scorecards and business reviews
• Plan and lead quarterly business reviews with partners, including usage analytics, product updates, and forward-looking roadmaps

Strategic Data Sourcing & Product Enablement (~40%)

• Serve as the primary point of contact for internal analytics and product teams seeking to leverage external data assets, advising on applicability, limitations, and best use cases
• Maintain accessible documentation, FAQs, and guidelines to enable self-service adoption across teams
• Partner with Data Engineering and Analytics teams to support onboarding, integration, and ongoing use of external data assets
• Monitor data quality, coverage, and performance, proactively identifying and resolving issues in partnership with internal and external stakeholders

Expanded Impact

• Identify and evaluate new external data sources and strategic partners to enhance internal analytics and product capabilities
• Align external data assets to high-priority business use cases, helping translate data capabilities into actionable insights and product features
• Support the integration of external data into analytics workflows and product development to drive measurable business impact

Required Qualifications

• 5+ years of experience in data product management, partnerships, business development, analytics operations, or a related field
• Demonstrated ability to manage complex, cross-functional initiatives with a degree of autonomy
• Strong communication skills — equally comfortable translating technical concepts for business audiences and business requirements for engineering teams
• Experience managing or supporting external client or partner relationships, ideally in a B2B data, analytics, or healthcare technology context
• Proficiency in SQL or equivalent data querying; comfort working with large, structured datasets
• Experience building and maintaining product or technical documentation
• Familiarity with data pipeline concepts, data schemas, and API-based data delivery

Preferred Qualifications

• Experience in healthcare data, claims data, or health analytics platforms
• Familiarity with third-party healthcare data assets (e.g., IQVIA, Komodo, HealthVerity, Datavant)
• Experience supporting or participating in commercial partnership discussions or deal processes
• Ability to independently run basic statistical analyses or data quality checks (Python, R, or SQL)
• Exposure to Agile methodologies and tools (Jira, Confluence, or similar)

Education

Bachelor's degree required, preferably in a quantitative, analytical, or technical field (Data Science, Statistics, Computer Science, Health Informatics, Economics, or related discipline).