Senior Data Scientist

Hims & Hers as a Senior Data Scientist, where you will drive technical execution and innovation within our data organization.

About Hims & Hers

Customer 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

Responsibilities

• You will translate complex business challenges into scalable data products and machine learning models, owning your projects from exploratory analysis to production deployment.
• Collaborate closely with Product, Engineering, and Business stakeholders to optimize operations, refine marketing efforts, and enhance the customer experience.
• You will also uphold engineering rigor and standards within the data team, mentor junior data scientists and analysts, and enjoy a range of benefits including generous PTO, full healthcare coverage, and a remote-first work environment.
• Prendre en charge l'exécution technique et l'innovation au sein de l'organisation des données, en traduisant des défis commerciaux complexes en produits de données robustes.
• Posséder l'ensemble du cycle de vie du modèle, de l'extraction des données et de l'ingénierie des fonctionnalités à la mise en production, aux tests A/B et à la surveillance des performances.
• Collaborer étroitement avec les équipes d'ingénierie, de produit et de finance pour définir les exigences techniques et traduire les résultats du modèle en informations commerciales claires et exploitables.

Requirements

• 5+ years of applied experience in Data Science or ML Engineering, with a track record of delivering production-ready models that drive measurable business value
• Education: BS, MS, or equivalent experience in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.)
• Analytical Problem Solving: Strong ability to connect technical metrics to business outcomes. You know how to choose the right algorithm for the right problem rather than just the most complex one
• Communication: Excellent ability to explain technical concepts, model limitations, and analytical findings to non-technical stakeholders
• Engineering Rigor: Proven ability to build for production. Experience working in cloud-based environments (AWS or GCP) and familiarity with CI/CD workflows, version control (Git), and ML Ops principles
• Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM)
• 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
• 0-to-1 Execution: Experience taking the very first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines
• 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

Preferred

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

Pay

GBP 75,000 - 95,000

Causal Inference: Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing