SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Hims & Hers, a leading health and wellness platform and NYSE-traded public company, is seeking a Senior Data Scientist to join their data organization in a fully remote role based in the EU.
You will be a core driver of technical execution and innovation, translating complex business challenges into robust, scalable data products and machine learning models. Operating with high autonomy, you will own projects end-to-end from exploratory analysis through production deployment, working closely with Product, Engineering, Finance, and Business stakeholders to deliver solutions that optimize operations, refine marketing efforts, and enhance customer experience.
Key responsibilities include:
- Building from scratch in 0-to-1 environments, writing complex SQL, engineering features, and deploying baseline models quickly to prove value before iterating toward complex solutions
- Owning the complete model lifecycle: data extraction, feature engineering, deployment, A/B testing, and performance monitoring
- Cross-functional collaboration with Engineering, Product, and Finance teams to define technical requirements and translate model outputs into actionable business insights
- Writing clean, modular, production-ready code and actively participating in peer code reviews
- Navigating technical ambiguity, breaking down complex requirements into manageable milestones
- Providing technical guidance and mentorship to junior data scientists and analysts
The role emphasizes engineering rigor, production-readiness, and the ability to connect technical metrics to measurable business outcomes. You will work in a culture that prioritizes diverse perspectives, ethics, wellness, and belonging.
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
- Strong expertise in Python and SQL; deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (PyTorch, XGBoost, LightGBM)
- Proven ability to build for production; experience in cloud-based environments (AWS or GCP); familiarity with CI/CD workflows, version control (Git), and ML Ops principles
- Strong analytical problem-solving ability; ability to connect technical metrics to business outcomes and choose the right algorithm for the problem
- Excellent communication skills to explain technical concepts, model limitations, and findings to non-technical stakeholders
- BS, MS, or equivalent experience in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.)
PREFERRED QUALIFICATIONS:
- Experience taking the first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines
- Advanced Business ML experience in one or more of: Customer Behavior & Propensity Modeling (churn, propensity-to-buy, lead scoring, LTV), Applied Forecasting (time-series, anomaly detection), Optimization (marketing spend, inventory, resource allocation), or Causal Inference (quasi-experiments, difference-in-differences)
