Staff Analyst, Product & Marketing

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve.

Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit hims.com/about and hims.com/how-it-works . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals .

About the Role:

As a Staff Analyst, Product & Marketing, you will serve as a strategic analytics partner to both the Product and Marketing organizations, driving impact across the full customer journey from acquisition and conversion to retention and growth. You will work cross-functionally with product managers, growth leads, category managers, marketing channel owners, designers, engineers, and data scientists in a fast-paced collaborative environment. Your expertise in A/B testing, digital analytics, marketing measurement, experimental design, and predictive modeling will allow Hims and Hers to optimize the customer experience and marketing investments in equal measure. This position will report to the Director of Product and Marketing Analytics.

You Will:

Provide thought leadership and strategic partnership to both Product and Marketing stakeholders, influencing roadmap and channel investment decisions with data-driven insights

Own the experimentation strategy across product and marketing workstreams, including test design, success metrics, sample-size estimation, guardrails, and results interpretation

Apply causal inference methods such as difference-in-differences and propensity score matching to move beyond correlation and identify what is actually driving metric movement

Partner with Data Science to contribute to predictive models, including churn, LTV, and conversion propensity, that directly inform product and marketing decisions

Own conversion funnel analytics end to end, identifying drop-off points, diagnosing root causes, and partnering with Product and Category teams to drive measurable improvements

Assess paid channel performance across SEM, Social, and CRM, and translate findings into clear investment and optimization recommendations, supporting incrementality testing and attribution work

Work cross-functionally with Data Science, Analytics Engineering, and Data Engineering teams to define tracking requirements and ensure data integrity across product and marketing workflows

Use Python or R alongside SQL to develop scalable analytical solutions and modeling outputs that go beyond what dashboards alone can answer

Design intuitive Looker dashboards that democratize data and elevate self-service capabilities across Product and Marketing teams

Segment users based on demographic, behavioral, and psychographic attributes to tailor product experiences, lifecycle communications, and marketing targeting

Champion data quality, documentation, and deliverable consistency while serving as a mentor to junior analysts

Create and maintain KPI frameworks and measurement plans for new features and initiatives

Conduct deep-dive analyses to answer strategic business questions, quantify opportunities, and recommend clear actions

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 across product and/or marketing environments

Experience partnering with Data Science to contribute to predictive models such as churn, LTV, or conversion propensity in Python or R

Extensive experience working with data engineering teams and production data pipelines