Staff Data Scientist (Machine Learning)

Location: Hybrid in London, England; compensation range stated for UK-based candidates

Salary: £95K–£115K per year, plus potential equity

Company

Hims & Hers is a public health and wellness platform delivering personalized healthcare from diagnosis through treatment and delivery.

What you will do

• Design and implement automated machine learning systems and core ML infrastructure.
• Translate ambiguous business questions around acquisition, churn, supply chain, and marketing attribution into actionable technical roadmaps.
• Lead the end-to-end deployment and lifecycle management of robust, maintainable production ML products.
• Partner with Engineering, Product, and Business to align technical strategy with measurable business outcomes.
• Establish model-development standards through design documentation, peer reviews, and reproducible practices.
• Mentor Senior and Mid-level Data Scientists and raise the technical bar across the data organization.

Requirements

• 8+ years of experience in Data Science or ML Engineering building production systems with measurable business impact.
• High proficiency in Python and SQL, with expert experience in pandas, NumPy, scikit-learn, and at least one major ML framework such as PyTorch, XGBoost, or LightGBM.
• Experience with CI/CD, MLOps, and the full model lifecycle in a cloud-based production environment using AWS or GCP.
• Ability to solve systemic problems, influence without authority, and communicate complex technical concepts to executive leadership.
• BS, MS, PhD, or equivalent expertise in a quantitative field such as Data Science, Statistics, Economics, Computer Science, or Applied Mathematics.
• Ability to work in a hybrid role based in London, England.

Nice to have

• Experience taking an organization’s first ML models from exploratory notebooks to automated production pipelines.
• Experience with customer behavior and propensity modeling, including churn, lead scoring, or lifetime value.
• Experience with forecasting, anomaly detection, optimization, or resource allocation.
• Experience designing causal inference studies such as quasi-experiments or difference-in-differences.

Culture & Benefits

• Equity may be included in the total rewards package.
• Commitment to diverse perspectives, ethics, wellness, and belonging.
• Talent-first flexible and remote work approach alongside the stated hybrid setup.
• Reasonable accommodations are available for qualified individuals with disabilities and disabled veterans.