Note: The job is a remote job and is open to candidates in USA. Hims & Hers is a health and wellness platform focused on providing personalized, accessible healthcare. The Staff Data Scientist will provide technical leadership across the data organization by building scalable machine learning systems, translating business needs into technical roadmaps, and delivering production-ready data products. The role also partners cross-functionally, establishes technical standards, owns model lifecycles, and mentors data scientists.
Responsibilities
- Architect the 0-to-1 Foundation: Lead the design and implementation of automated ML systems. You know how to balance "doing it right" with "doing it fast," making pragmatic architectural choices (build vs. buy, simple vs. complex) while rolling up your sleeves to write production code and establish our core ML infrastructure
- 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 Business 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 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
- Mentorship & Coaching: Actively mentor Senior and Mid-level Data Scientists, elevating the technical bar and fostering a culture of continuous learning across the data organization
Skills
- 8+ years of experience in Data Science or ML Engineering, with a proven track record of building production systems that deliver measurable business impact
- 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)
- 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
- Proven ability to influence without authority. You can translate complex technical logic into compelling narratives for executive leadership
- Experience with CI/CD, ML Ops, and managing the full lifecycle of models in a cloud-based production environment (AWS or GCP)
- BS, MS, or PhD in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.) or equivalent field expertise
- Experience taking the very first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines
- Building predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions
- Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning
- Building engines for marketing spend, inventory management, or resource allocation
- Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing
Benefits
- Equity compensation for full-time roles
- Unlimited PTO
- Company holidays
- Quarterly mental health days
- Comprehensive health benefits including medical, dental & vision
- Parental leave
- Employee Stock Purchase Program (ESPP)
- 401k benefits with employer matching contribution
- Offsite team retreats
Company Overview
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