Senior Data Scientist at Hims & Hers

Hims & Hers is the leading health and wellness platform, redefining healthcare by delivering accessible, affordable, and personalized care from diagnosis to treatment. They operate as a public company, traded on the NYSE under the ticker symbol “HIMS.”

About the Role:

As a Senior Data Scientist at Hims & Hers, you will drive technical execution and innovation within the data organization. You will tackle complex business challenges and translate them into robust, scalable data products and machine learning models. This role requires high autonomy, with ownership of projects from exploratory analysis to production deployment.

You will collaborate closely with Product, Engineering, and Business stakeholders to optimize operations, refine marketing efforts, and enhance customer experience. Your responsibilities include building powerful models and upholding engineering rigor and standards within the data team.

You Will:

• Build from Scratch: Thrive in a 0-to-1 environment by writing complex SQL, engineering features, and deploying baseline models (heuristics or simple ML) quickly to prove value before iterating toward complex solutions.

• End-to-End Execution: Own the complete model lifecycle, including data extraction, feature engineering, deployment, A/B testing, and ongoing performance monitoring.

• Cross-Functional Collaboration: Partner with Engineering, Product, and Finance teams to define technical requirements and translate model outputs into actionable business insights.

• Uphold Technical Standards: Write clean, modular, and production-ready code, participate in peer code reviews, and contribute to technical best practices.

• Drive Project Delivery: Navigate technical ambiguity, breaking down complex project requirements into manageable milestones.

• Team Mentorship: Provide technical guidance and support to junior data scientists and analysts, helping them troubleshoot and adopt best practices.

Experience & Skills:

• 5+ years of applied experience in Data Science or ML Engineering, delivering production-ready models with measurable business value.

• Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (PyTorch, XGBoost, LightGBM).

• Engineering Rigor: Experience building for production, working in cloud environments (AWS or GCP), and familiarity with CI/CD workflows, Git, and ML Ops principles.

• Analytical Problem Solving: Ability to connect technical metrics to business outcomes and choose the right algorithm for the problem.

• Communication: Excellent ability to explain technical concepts, model limitations, and findings to non-technical stakeholders.

• Education: BS, MS, or equivalent experience in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.).

Preferred Qualifications:

• 0-to-1 Execution: Experience taking initial ML models from exploratory notebooks to reliable, automated production pipelines.

• Advanced Business ML: Experience in 1-2 of the following areas:

  • Customer Behavior & Propensity Modeling: Predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to 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).