Senior Data Product Manager

Komodo Health is a healthcare data and technology company focused on reducing the global burden of disease through its Healthcare Map and software applications. The Senior Data Product Manager will drive the strategy, discovery, development, and execution of core data products, partnering with engineering, product, and commercial teams to deliver high-value healthcare data solutions.

Responsibilities:

• Work with engineers to drive our product strategy and execution on Komodo’s growing suite of data products
• Collaborate with engineering leadership to help craft our technical strategy based on your deep understanding of our platform and customer needs
• Partner closely with our product principal and commercial teams to document use cases, create requirements, design evaluation criteria, and ensure on-time, high-value analysis
• Own the day-to-day responsibilities for sprint management and ensure that the team is operating at high levels of efficiency
• Ensure collaboration with teams throughout the organization, and will help to share knowledge throughout the company

Requirements:

• 9+ years of experience in a data-focused product role at a healthtech/saas, or similar company
• Prior experience working with and translating US healthcare/medical/claims data into requirements for life science customers
• Real technical depth, including the ability to write and understand SQL, reason about data models and pipelines, and engage substantively with engineers on tradeoffs rather than relaying messages between them and the business
• Working knowledge of the core concepts behind statistical data analysis, and the judgment to notice when they are being misapplied
• Fluency with AI tools as part of how the work actually gets done, including exploring unfamiliar datasets, prototyping concepts, drafting and pressure-testing requirements, and challenging their own reasoning
• Ability to leverage AI tools (Claude, Cursor, etc.) to enhance personal productivity, streamline workflows, and process large amounts of data
• Curiosity about how data and systems are built and where they break, paired with the drive to go find the answer and comfort in not knowing something for a while
• A bias toward the simple version, with the patience to sit with an ambiguous problem and ask the question that reframes it rather than shipping the first workable answer
• The ability to break a conceptual goal into smaller, actionable pieces, with enough attention to detail to define what "done" and "good" mean before work starts