Staff Data Scientist
Quick Summary
0-to-1 Execution: Experience taking the very first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines.
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
~1 min readAs a Staff Data Scientist at Hims & Hers, you are a technical leader and a "force multiplier" for our data organization. You do not just solve the most difficult problems; you identify which problems are worth solving to move the needle for our customers. You will serve as a technical anchor, simplifying ambiguous problems into executable paths for the team.
In this role, you will bridge the gap between business strategy and production-ready machine learning. Whether you are building frameworks for growth, optimizing our supply chain, or refining marketing attribution, you will ensure our data products are technically sound, scalable, and built to deliver measurable business results.
Requirements
~2 min readCustomer Behavior & Propensity Modeling: Building predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions.
Applied Forecasting: Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning.
Optimization: Building engines for marketing spend, inventory management, or resource allocation.
Causal Inference: Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing.
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.
Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at accommodations@forhims.com and describe the needed accommodation. Your privacy is important to us, and any information you share will only be used for the legitimate purpose of considering your request for accommodation. Hims & Hers gives consideration to all qualified applicants without regard to any protected status, including disability. Please do not send resumes to this email address.
To learn more about how we collect, use, retain, and disclose Personal Information, please visit our Global Candidate Privacy Statement.
Location & Eligibility
Listing Details
- Posted
- September 11, 2026
- First seen
- September 25, 2026
- Last seen
- September 25, 2026
Posting Health
- Days active
- 0
- Repost count
- 1
- Trust Level
- 16%
- Scored at
- September 25, 2026
Signal breakdown
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