Sr Analyst, AI Analytics

Hims & Hers•,

2d•$120,000 - $160,000

About The Position

As a Sr Analyst, AI Analytics, you will serve as a trusted analytics partner to the teams building and operating Hims & Hers' AI products, including patient-facing AI chat assistants and 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 design rigorous experiments and measurement plans for AI-driven experiences. You will operate with high autonomy and report to the Sr Manager of AI Analytics.

Requirements

At least 5 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.
At least 3 years of experience designing, executing, and analyzing A/B tests.
Experience working with data engineering and analytics engineering teams, including dbt-modeled production pipelines.
Solid grounding in experimental design and statistical inference, with exposure to causal inference beyond standard A/B testing, such as quasi-experimental methods or observational study design.
Experience with subscription-based business models and metrics, including cohort analysis, retention and churn analysis, and addressability sizing.
Strong SQL skills; BigQuery is preferred.
Working knowledge of Python or R.
Advanced experience with Looker or Tableau.
Ability to explain technical analyses clearly to non-technical audiences, including senior leadership.
Experience translating analysis into recommendations that change product decisions.
Proactive, ownership-driven mindset; strong organizational and prioritization skills; and comfort with ambiguity.

Nice To Haves

Experience evaluating conversational AI or LLM-based products, including intent classification, containment and escalation, and 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, such as lifelines, pyfixest, or statsmodels.
Experience with dbt, Airflow, and Databricks.

Responsibilities

Deliver data-driven insights and recommendations on AI product performance to inform product roadmap and investment decisions.
Design and analyze tests for AI product launches and iterations, including success metrics, sample-size estimation, guardrails, and interpretation of results.
Use quasi-experimental methods, including difference-in-differences, fixed-effects models, and propensity score matching, to assess AI impact when randomized tests are not feasible.
Define and validate metrics and measurement plans for new AI product use cases, from pre-launch instrumentation through post-launch readouts.
Partner with ML and Applied AI teams to evaluate model performance in production and translate model-level signals into product and business metrics.
Analyze cost savings, handle-time efficiency, support deflection, and retention and churn addressability for AI initiatives.
Work 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 analytical solutions beyond dashboard reporting, such as observational studies and survival or retention modeling.
Design intuitive Looker dashboards that make AI product metrics accessible to Product and Care Operations teams.
Conduct deep-dive analyses, including user and session segmentation, to identify AI product performance patterns and opportunity areas and recommend actions.