Staff Data Scientist

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 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.

You Will

• Build Scalable Solutions: Lead the design and delivery of ML systems and data products that directly impact company-wide growth and operational strategy
• Translate Business Needs: Turn ambiguous business questions (from customer acquisition to churn dynamics) into concrete technical roadmaps that deliver clear, actionable results
• Drive Execution and Reliability: Lead the end-to-end deployment of ML products, ensuring they are not just accurate but robust, maintainable, and fully integrated into our production infrastructure
• Connect Technical & Business Goals: Partner across Engineering, Product, and Finance to ensure our technical strategy is solving the right business problems and moving our core metrics
• Define Technical Standards: Act as a force multiplier by establishing the standards for model development. You will lead design docs and peer reviews that ensure our work is reproducible and integrates seamlessly with the work of our Data and Analytics Engineering partners
• Own the Results: Take accountability for the full model lifecycle, from the initial data design through to the long-term performance and business value of production systems

You Have

• 8+ years of experience in Data Science or ML Engineering, with a proven track record of building production systems that deliver measurable business impact
• Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM)
• Systemic Problem Solving: Ability to work on unique issues requiring conceptual thinking and broad impact. You know how to build for long-term scalability while delivering immediate value
• Leadership & Influence: Proven ability to influence without authority. You can translate complex technical logic into compelling narratives for executive leadership
• Engineering Rigor: Experience with CI/CD, ML Ops, and managing the full lifecycle of models in a cloud-based production environment (AWS or GCP)
• Education: BS, MS, or PhD in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.) or equivalent field expertise

Preferred Qualifications

• Forecasting Expertise: Specialization in time-series analysis, probabilistic forecasting, and handling non-stationary data in high-growth environments
• Optimization & Operations Research: Experience building optimization engines for marketing spend, inventory management, or resource allocation
• Causal Inference: Expertise in experimental design beyond standard A/B testing, including quasi-experiments and structural equation modeling

Our Benefits (there are more but here are some highlights):

• Competitive salary & equity compensation for full-time roles
• Unlimited PTO, company holidays, and quarterly mental health days
• Comprehensive health benefits including medical, dental & vision, and parental leave
• Employee Stock Purchase Program (ESPP)
• 401k benefits with employer matching contribution
• Offsite team retreats

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.

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