Staff Analyst, AI Product

About the Role:

As a Staff Analyst, AI, you will serve as a strategic analytics partner to the teams building and operating Hims & Hers' AI products (e.g., patient-facing AI chat assistants, internal AI tools for care teams). You will work cross-functionally with engineers, product managers, clinical operations, and finance to measure product performance, quantify commercial and clinical impact, and shape the experimentation and measurement strategy for AI-driven experiences. This position will report to the Manager of AI Analytics.

You Will:

• Provide thought leadership and strategic partnership to AI Product stakeholders, influencing roadmap and investment decisions with data-driven insight into AI product performance
• Own experimentation strategy for AI product launches and iterations (e.g., GrowthBook-based tests), including test design, success metrics, sample-size estimation, guardrails, and results interpretation
• Apply causal inference and quasi-experimental methods — including fixed-effects models, difference-in-differences, and propensity score matching — to assess AI impact on retention and clinical/operational outcomes when randomized tests aren't feasible
• Define, validate, and own metrics frameworks and measurement plans for new and evolving AI product use cases — from pre-launch instrumentation through post-launch readouts — translating ambiguous business questions into rigorous, well-instrumented metrics within a complex, multi-source data environment
• Partner with ML/Applied AI teams to evaluate model performance in production and translate model-level signals (confidence, escalation type, resolution outcome) into product and business metrics
• Own commercial impact analysis for AI products — cost savings, handle-time efficiency, and support deflection — and quantify retention/churn addressability to size the impact of AI initiatives
• Work cross-functionally with AI/ML Engineering, Analytics Engineering, and Data Engineering teams to define tracking requirements and ensure data integrity across AI product pipelines and event schemas
• Use Python or R alongside SQL to develop scalable analytical solutions (e.g., observational studies, survival/retention modeling) that go beyond what dashboards alone can answer
• Design intuitive Looker dashboards that democratize AI product metrics and elevate self-service across Product and Care Operations teams
• Conduct deep-dive analyses — including user/session segmentation — to answer strategic questions about AI product performance, identify where AI products are (and aren't) working, quantify opportunity areas, and recommend clear actions
• Champion data quality, documentation, and deliverable consistency across dbt models and BigQuery tables that power AI metrics, while mentoring junior analysts

You Have:

• 8+ years of experience in analytics, data science, or a related quantitative field
• Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or a related field
• 5+ years of experience designing, executing, and analyzing A/B tests, ideally including tests on AI/ML-driven product experiences
• Experience partnering with ML teams to evaluate model outputs and translate them into product/business metrics (e.g., classification accuracy, confidence scores, resolution quality)
• Extensive experience working with data engineering and analytics engineering teams, including dbt-modeled production pipelines
• Strong knowledge of experimental design and statistical inference; experience applying causal inference techniques beyond standard A/B testing, such as quasi-experimental methods or observational study design (e.g., fixed-effects regression, survival analysis)
• Experience with subscription-based business models and metrics, including cohort analysis, retention/churn analysis, and addressability sizing
• Expert SQL skills (BigQuery preferred) and advanced experience with Looker or Tableau
• Ability to explain technical analyses clearly to non-technical audiences, including senior leadership
• Experience shaping and influencing product strategy, not just executing analyses
• A proactive, ownership-driven mindset with strong organizational and prioritization skills

Preferred Qualifications:

• Experience evaluating conversational AI or LLM-based products (intent classification, containment/escalation, hallucination or quality monitoring)
• Familiarity with telehealth concepts or subscription-based healthcare models, including clinical safety considerations in AI-assisted workflows
• Experience with GrowthBook or a comparable experimentation platform
• Experience with survival analysis or time-to-event modeling (e.g., lifelines, pyfixest, statsmodels)
• dbt, Airflow, and Databricks experience