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Role Description

As Senior Product Manager, Life Sciences Data Products, you will own the strategy and execution for a portfolio of data-driven products used by life sciences customers to find, access, evaluate, and operationalize complex clinical datasets for R&D and clinical development workflows.

• Define the life sciences product strategy, identify the highest-leverage problems, and translate them into a sequenced roadmap with measurable outcomes.
• Run customer interviews, workflow mapping, and opportunity sizing to determine what to build, what to standardize, and what to avoid as one-off services.
• Build repeatable “productized” capabilities that improve dataset usability, governance, search/retrieval, cohort building, and downstream analytics readiness.
• Partner with technical teams to design automation that reduces friction in data access and analysis (e.g., metadata enrichment, quality signals, dataset packaging, evaluation tooling).
• Write requirements, define success metrics, manage tradeoffs, and drive delivery from concept through launch—iterating based on usage and customer outcomes.
• Collaborate closely with go-to-market partners to ensure positioning, packaging, and feedback loops inform the roadmap without turning the product into custom projects.
• Stay current on life sciences R&D and clinical development trends and incorporate them into differentiation and product choices.

Qualifications

• 5+ years building data products or platforms for life sciences and/or healthcare customers.
• Strong product discovery muscle: customer interviews, problem framing, prioritization, and roadmap ownership.
• Technical fluency across data infrastructure, APIs, pipelines, and working concepts in ML-enabled products (no need to code).
• Track record partnering with engineering and data teams to deliver complex, high-impact product work.
• Excellent communication—credible with technical teams and clear with non-technical stakeholders.
• Comfort operating in a fast-moving environment with evolving inputs and limited process.

Requirements

• 0→1 product experience or taking early products to scale in a regulated domain.
• UX/product design sensibility with strong intuition for end-user workflows.
• Prior experience in analytics, data science, or experimentation.
• Familiarity with privacy, governance, and quality frameworks for sensitive datasets.

Benefits

• Competitive base + equity + benefits. (Exact range varies by level and location and will be shared during the process.)