About the RoleHippocratic AI is looking for a Lead Product Data Analyst to shape product strategy and measure the clinical, operational, and financial impact of our healthcare AI products. This isn't a dashboarding role - you'll help define what "good" looks like for AI clinical agents (including critic frameworks and quality criteria), not just track adoption of a finished product.
You'll partner with Product, Engineering, Customer Success, clinical teams, and leadership to answer questions like: What should we build? What's driving or limiting adoption? What outcomes are we creating for patients and customers? Where should we invest next - and how do we prove it with data?
The ideal candidate moves comfortably from an ambiguous business question to structured analysis to an executive-ready recommendation, and has the business judgment to know which questions matter most.
What You'll DoDefine how we measure success- Partner with clinical and product teams to define AI agent performance criteria, including critic frameworks and quality metrics.
- Define north star metrics and measurement frameworks that guide product strategy - not just measure what already exists.
- Design analytical approaches to evaluate product changes and program impact, including in real-world settings where randomized experiments aren't possible.
- Conduct pre- and post-launch analysis to determine whether initiatives achieved their intended outcomes.
Turn data into decisions and dollars- Translate ambiguous product and business questions into structured analysis and clear recommendations that influence roadmap and prioritization.
- Build business cases and ROI models connecting product usage to operational efficiency, cost reduction, capacity, and patient/customer outcomes.
- Partner with technical teams to improve instrumentation so the data behind these decisions is reliable.
Represent the work - internally and with customers- Present findings and recommendations (not just metrics) to Product leadership and executives.
- Sit directly in customer and partner conversations to represent product data, outcomes, and ROI - this isn't just internal deck prep.
- Serve as a strategic analytics partner across Product, Engineering, Customer Success, and GTM, and help raise the analytical bar as we scale.
Location RequirementWe believe the best ideas happen together. To support fast collaboration and a strong team culture, this role is expected to be in our Menlo Park office five days a week, unless otherwise specified.
What You BringMust-have- 5+ years in product analytics, product strategy, data analytics, business strategy, or management consulting.
- Bachelor's degree in a quantitative or analytical discipline (Business, Economics, Finance, Statistics, Data Science, CS, Engineering, or related).
- Advanced SQL and demonstrated ability to independently analyze large, complex datasets; working Python proficiency preferred.
- Demonstrated experience using data to influence product strategy, prioritization, or roadmap decisions.
- Experience with product analytics/BI tools (Looker, Tableau, Metabase, or similar).
- Design analytical approaches to evaluate product changes and program impact - including in real-world settings where randomized experiments aren't possible.
- Experience building business cases, ROI analyses, or financial models, and presenting them to senior stakeholders.
Nice-to-Have- Experience in product analytics or strategy at a technology, healthcare technology, SaaS, or AI company.
- Experience working with healthcare data, products, clinical workflows, or healthcare organizations.
- Fluency in healthcare financial and value-based care concepts (e.g., HRRP/readmission economics, value-based care arrangements, risk-based contracting).
- Experience designing causal, cohort, funnel, retention, or behavioral analyses, especially where RCTs aren't feasible.
- Experience presenting to Director/VP/C-suite or senior customer stakeholders.
- Experience with AI, machine learning, or LLM-powered products.
- Startup or high-growth experience where responsibilities extend beyond a narrowly defined analytics function.
What Success Looks LikeSuccess here isn't how many dashboards you build - it's whether your analysis changes a decision. You'll help us understand which product investments matter most, which capabilities create measurable value, and how to prove it with data.
