Lead Product Data Analyst (AI)

Location: On-site in Menlo Park, California, United States; five days per week

Company

Hippocratic AI builds a safety-focused, healthcare-only large language model and AI platform designed to improve patient outcomes.

What you will do

• Establish company-wide evaluation frameworks, critic architectures, quality baselines, North Star metrics, and multi-tier measurement strategies for AI clinical agents.
• Design pre- and post-launch analyses and real-world evaluation methods when randomized experiments are not feasible.
• Build analytical solutions and financial models connecting product adoption with health system ROI, clinical outcomes, cost reduction, and value-based care performance.
• Improve product instrumentation and data reliability with technical teams.
• Present analytical findings and ROI models to executive leaders, healthcare customers, and partners.
• Set product analytics standards, mentor colleagues, and influence product roadmaps and capital allocation.

Requirements

• 6–8+ years of progressive experience in product analytics, product strategy, data analytics, business strategy, or management consulting in high-growth technology or healthcare environments.
• Bachelor’s degree in a quantitative or analytical discipline.
• Advanced SQL and experience independently analyzing large, complex datasets; working Python proficiency is preferred.
• Experience influencing company-wide product strategy, roadmaps, and investment decisions with data.
• Experience with product analytics or BI tools such as Looker, Tableau, or Metabase.
• Experience building ROI models, conducting causal, cohort, funnel, or retention analyses, and presenting to VP, C-suite, or senior customer stakeholders.

Nice to have

• Healthcare data, clinical workflow, healthcare organization, or value-based care experience.
• Experience with AI, machine learning, or LLM-powered products.
• Startup or high-growth company experience.

Culture & Benefits

• Collaborative in-office environment supporting close cross-functional work.
• Work alongside physicians, hospital leaders, AI researchers, and technology experts.
• Build safety-focused healthcare AI intended to improve patient outcomes at scale.
• Equal opportunity workplace with accommodations available during the hiring process.