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Hippocratic AI is seeking a Product Data Analyst to shape product strategy and measure the clinical, operational, and financial impact of healthcare AI products. This role goes beyond dashboarding—you'll help define success metrics for AI clinical agents, including critic frameworks and quality criteria, and guide product investment decisions with data.
You will partner with Product, Engineering, Customer Success, clinical teams, and leadership to answer critical questions: 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?
Key responsibilities include:
• Define how success is measured by partnering with clinical and product teams to establish AI agent performance criteria, critic frameworks, and quality metrics that guide product strategy rather than just track existing usage.
• Design analytical approaches to evaluate product changes and program impact, including in real-world settings where randomized experiments aren't feasible.
• Conduct pre- and post-launch analysis to determine whether initiatives achieved intended outcomes.
• Translate ambiguous product and business questions into structured analysis and clear recommendations that influence roadmap and prioritization decisions.
• 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 data instrumentation and reliability.
• Present findings and recommendations to Product leadership and executives, not just metrics dashboards.
• Sit directly in customer and partner conversations to represent product data, outcomes, and ROI.
• Serve as a strategic analytics partner across Product, Engineering, Customer Success, and GTM functions.
The ideal candidate moves comfortably from ambiguous business questions to structured analysis to executive-ready recommendations, with strong business judgment about which questions matter most.
Company context: Hippocratic AI is building the world's first healthcare-only, safety-focused LLM platform designed to transform patient outcomes at scale. Co-founded by CEO Munjal Shah and a team of physicians, hospital leaders, and AI pioneers from institutions including Johns Hopkins, Stanford, Google, Meta, Microsoft, and NVIDIA. Recently raised $126M Series C at $3.5B valuation, with total funding of $404M from investors including CapitalG, General Catalyst, a16z, Kleiner Perkins, and leading healthcare systems.
Location: Menlo Park office, five days per week.
REQUIREMENTS
Must-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)
• Ability to 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
