Director, Product & Marketing Analytics

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. As Director of Product & Marketing Analytics, you will define how Hims & Hers measures and acts on the performance of its core products and marketing investments, leading a team of analysts to turn complex data into clear decisions.

Responsibilities:

• Serve as the analytics thought partner to GMs, VPs of Product, and Marketing leadership, shaping roadmaps and investment decisions through data
• Represent analytics in cross-functional forums, translating technical findings into executive-ready narratives and influencing decisions at the C-suite level
• Maintain visibility into macro-level business sensitivities: e.g., how a 2.5pp shift in retention translates to quarterly and annual revenue impact
• Own retention analytics across the subscription lifecycle, including cohort design, churn window decomposition, and segment-level intervention prioritization (product type, WL prior experience, check-in engagement, dose adjustment)
• Define hero metrics, guardrail metrics, and dashboard frameworks to monitor performance across membership and Rx subscription populations in real time
• Design experimental and observational analyses to identify causal drivers of retention and churn, and translate findings into CRM, product, and clinical interventions
• Partner with product and clinical teams on evaluation of new features and treatment protocols, side-effect management, check-in experience, snooze/save mechanics
• Guide segmentation strategy across user attributes to prioritize where retention investment has the highest ROI
• Lead the transition from MTA to MTI (Multi-Touch Incrementality), including MMM validation, incrementality test design (geo holdouts, go-dark tests), cross-category halo methodology, and calibration aligned to quarterly finance targets
• Partner with Marketing leadership to assess paid channel efficiency across SEM, Social, OTT TV, Podcast, and emerging channels, with a clear view of where MTI and MTA diverge and why
• Inform media mix decisions by quantifying cross-category halo effects and identifying where paid efficiency assumptions may be under- or overstated
• Support A/B experiment design and analysis across CRM and marketing channels, including AI Decisioning pilots
• Lead and develop a team of analysts, setting standards for rigor, documentation, experimentation methodology, and deliverable quality
• Collaborate with Data Platform Engineering to define data model requirements, customer state snapshots, dosage/titration tables, retention PDTs
• Ensure dashboards and self-serve assets are high-quality, well-documented, and actively used; drive Looker and GrowthBook adoption across product and marketing teams
• Champion causal inference over correlation, actionable insight over descriptive reporting, and clear uncertainty communication
• Manage FTE allocation across competing workstreams with real-time reallocation to high-urgency questions

Requirements:

• 12+ years in analytics, data science, or a related quantitative field; at least 3 years in a senior or lead role
• Bachelor's in Statistics, Mathematics, Economics, Computer Science, Engineering, or related field; advanced degree a plus
• Experience leading analytics teams in a fast-paced consumer product environment, ideally subscription or DTC
• Deep expertise in experimental design, A/B testing, holdout groups, and causal inference methods
• Deep experience with MMM and incrementality testing; comfort navigating disagreements between models
• Strong command of retention and subscription analytics: cohort analysis, churn decomposition, LTV modeling
• Expert SQL and experience with large-scale data warehouses (BigQuery, Snowflake, or equivalent)
• Fluency with BI and experimentation platforms such as Looker, GrowthBook, or Tableau
• Proven ability to communicate complex findings to non-technical executive audiences
• Strong organizational skills, managing long-horizon projects while responding to time-sensitive needs
• Experience with telehealth, pharmaceutical, or health subscription business models
• Familiarity with WL therapeutics, clinical pathways, or subscription-based Rx fulfillment
• Experience with AI-driven decisioning or personalization platforms (e.g., Hightouch, Braze)
• Experience with Python or R for statistical modeling
• Experience with dbt, Databricks, Airflow, or similar data tooling
• Exposure to price testing, elasticity modeling, or subscription economics research