Senior Product Manager, Data Profiles

Spring Health is hiring a Senior Product Manager to lead the strategy and roadmap for its Data Profiles team in the R&D organization. The role builds a data foundation for personalized care by enabling common access to member data, developing personalization signals, and evaluating and integrating external data sources.

Responsibilities:

• Own the vision, strategy and roadmap for Data Profiles across its three areas: production data access, personalization signals, and external data integration
• Partner with software engineers to define and ship a common API layer that lets product teams reliably access member data in production to personalize experiences, and drive its adoption across Spring
• Partner with data scientists to find, test and put into production the personalization signals that come from data across our warehouse and production systems. Set clear hypotheses, success metrics and quality bars for each one
• Develop and run a strategy for evaluating, choosing and integrating external data sources
• Run continuous discovery with internal teams that use Data Profiles (product, engineering, clinical, data science) and turn their needs into one prioritized roadmap. Communicate tradeoffs and progress clearly to stakeholders at every level
• Set standards for profile data (definitions, freshness, accuracy, governance) together with clinical, legal, privacy and security partners, so member data is trustworthy, reusable and used responsibly
• Measure and report how the platform affects downstream teams and member outcomes, and use that data to decide where to invest next

Requirements:

• 4+ years of product management experience, including 2+ years on data, platform or API products used by internal or external developers
• Experience shipping data products into production: data pipelines, feature or profile stores, customer data platforms (CDPs) or personalization systems
• Strong data and ML fluency: you can work with data scientists on feature engineering, signal quality, model evaluation and experiment design
• The technical depth to engage with engineers on API design, data models, latency, scalability and system tradeoffs
• Comfort working directly with data, through SQL or similar, to answer your own questions
• Experience evaluating or integrating third-party data sources, including weighing vendors and making build-vs-buy decisions
• Strong skills in aligning technical, clinical and business stakeholders with competing priorities
• Sound judgment about privacy, consent and responsible data use
• Prior experience as a data scientist or machine learning engineer
• Experience in healthcare, mental health or benefits, including working with protected health information (PHI) under HIPAA
• Familiarity with modern data stack tools (e.g., Snowflake/Databricks, dbt, streaming systems, feature stores)