Staff Data Scientist

Hims & Hers as a Staff Data Scientist, where you will be a technical leader and a "force multiplier" for our data organization. You will bridge the gap between business strategy and production-ready machine learning, ensuring our data products are technically sound, scalable, and built to deliver measurable business results. You will lead the design and implementation of automated ML systems, translate ambiguous business questions into concrete technical roadmaps, and drive the end-to-end deployment of ML products. Additionally, you will mentor and coach senior and mid-level data scientists, fostering a culture of continuous learning across the data organization.

About Hims & Hers

Leadership & Influence: Proven ability to influence without authority. You can translate complex technical logic into compelling narratives for executive leadership

Responsibilities

• Architect the design and implementation of automated machine learning systems, balancing quality and speed.
• Translate ambiguous business questions into concrete technical roadmaps that deliver clear, actionable results.
• Lead the end-to-end deployment of machine learning products, ensuring they are accurate, robust, maintainable, and fully integrated.

Requirements

• 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
• Education: BS, MS, or PhD in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.) or equivalent field expertise
• 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)
• 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
• Causal Inference: Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing

Preferred

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

Pay

GBP 95,000 - 115,000

• Engineering Rigor: Experience with CI/CD, ML Ops, and managing the full lifecycle of models in a cloud-based production environment (AWS or GCP)
• 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
• Optimization: Building engines for marketing spend, inventory management, or resource allocation