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Komodo Health is building the Healthcare Map, the industry's largest and most complete view of the U.S. healthcare system by combining de-identified real-world patient data with innovative algorithms and clinical expertise. The company partners with organizations across the healthcare ecosystem to improve patient care and reduce disease burden through data-driven insights.
As a Senior Data Product Manager, you will drive the development and innovation of Komodo's core data products. You'll partner with engineering leadership to craft technical strategy based on deep platform and customer understanding, working closely with the product principal and commercial teams to document use cases, create requirements, and design evaluation criteria. Your responsibilities include sprint management, ensuring team efficiency, and fostering cross-functional collaboration.
Key expectations include developing fluency in the company's data through a customer lens, leading discovery into customer use cases and building evidence-based perspectives on competitive positioning, shipping marked improvements to core data products, identifying and validating new product opportunities, building a prioritized evidence-backed backlog, and earning trust as a thought partner to Data Engineering and commercial teams.
You should bring experience in data-focused roles at B2B technology or software companies, with prior product management experience strongly preferred. Real technical depth is essential—you'll need to write and understand SQL, reason about data models and pipelines, and engage substantively with engineers on technical tradeoffs. Working knowledge of statistical data analysis concepts, experience with US healthcare data, and understanding of life sciences team needs are important. You're curious about how data systems are built and where they break, with a bias toward simple solutions and the patience to work through ambiguous problems. You excel at breaking conceptual goals into actionable pieces with clear definitions of done and good. Finally, you should be fluent with AI tools as part of your workflow, using them to explore datasets, prototype concepts, draft requirements, and challenge your own reasoning.
