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Staff Analyst (Artificial Intelligence)

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Onsite

Staff Analyst (Artificial Intelligence)

Hims & Hers

Staff Analyst (Artificial Intelligence)

Skills

SQL QueriesLookerData EngineeringTableauPythonProduct StrategyData ScienceRDatabricksData AnalysisMachine LearningAIdbtApache Airflow

2 months ago

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Important information


Contract type:

Permanent

Salary:

$155,000 – $190,000 / year

Location:

United States

Work mode:

Onsite

Published on:

10 September 2026

What they need


  • 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
  • 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

Benefits

  • Generous PTO: Take the time you need, when you need it - including generous parental leave
  • Full healthcare: High-coverage medical, dental & vision coverage for individuals and families
  • Retirement planning: Take advantage of our 401(k) plan including contribution matching
  • Work from anywhere: We are a remote-first company, so you can work from anywhere you like in the uS
  • Robust compensation: We offer competitive salary bands and stock options
  • Employee discount: Employees can take advantage of product discounts
  • Utility stipend: A extra $75 each month to cover extra cell phone, internet, or data usage
  • Spending accounts: Options for additional HSA and FSA plans to help toward healthcare costs- 8+ years of experience in analytics, data science, or a related quantitative field
  • Experience partnering with ML teams to evaluate model outputs and translate them into product/business metrics (e.g., classification accuracy, confidence scores, resolution quality)
  • 5+ years of experience designing, executing, and analyzing A/B tests, ideally including tests on AI/ML-driven product experiences
  • 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
  • Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or a related field
  • Ability to explain technical analyses clearly to non-technical audiences, including senior leadership
  • 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)
  • A proactive, ownership-driven mindset with strong organizational and prioritization skills
  • Experience shaping and influencing product strategy, not just executing analyses
  • We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. If you’re excited about this role, we encourage you to apply—even if you’re not sure if your background or experience is a perfect match
  • Experience with GrowthBook or a comparable experimentation platform
  • Familiarity with telehealth concepts or subscription-based healthcare models, including clinical safety considerations in AI-assisted workflows
  • Experience evaluating conversational AI or LLM-based products (intent classification, containment/escalation, hallucination or quality monitoring)
  • Experience with survival analysis or time-to-event modeling (e.g., lifelines, pyfixest, statsmodels)
  • Dbt, Airflow, and Databricks experience

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