Hims & Hers — the leading health and wellness platform traded on the NYSE under the ticker HIMS, on a mission to help the world feel great through the power of better health — is seeking a Staff Data Scientist for its London, UK team on a hybrid work basis. This senior technical leadership role pays £95,000–£115,000 plus equity and requires a minimum of 8+ years of Data Science or ML Engineering experience with a proven track record of building production ML systems that deliver measurable business impact. You will serve as a technical anchor and force multiplier for the data organization — architecting 0-to-1 ML foundations, translating business questions into technical roadmaps, leading end-to-end ML product deployment, and mentoring senior and mid-level data scientists across Hims & Hers’ Analytics & Data Science department.
Compensation & Benefits — Staff Data Scientist, London UK
Base Salary: £95,000 – £115,000 per year — competitive senior data science leadership compensation for the London market
Equity: Equity grant included — meaningful ownership stake in a NYSE-listed public health technology company (HIMS)
Work Model: Hybrid — London, England office with flexible remote work approach
Total Rewards: Comprehensive Total Rewards package including equity, benefits, and wellness-aligned culture at a health and wellness company
Salary Note: Exact amount determined by skill sets, experience, certifications, and location factors — target range for UK-based candidates
About Hims & Hers — NYSE-Listed Health & Wellness Platform
Company: Hims & Hers (NYSE: HIMS) — Leading Health & Wellness Platform | Redefining Healthcare | Customer-First · Affordable · Accessible · Personal
Mission: Help the world feel great through the power of better health — from diagnosis to treatment to delivery, making personalized care designed for results accessible to everyone
Data Focus: Analytics & Data Science department — data and ML are central to customer acquisition, churn management, supply chain optimization, and marketing attribution strategy
Culture: Talent-first · Flexible/remote-friendly · Ethics and wellness prioritized · Diverse and inclusive workforce | Commitment to continuous learning
Scale: Public company (NYSE: HIMS) — production ML systems operating at scale across a growing global health and wellness customer base
Why This Hims & Hers Staff Data Scientist Role in London Is a Career-Defining Opportunity
Force Multiplier Status: The Staff Data Scientist designation at Hims & Hers is specifically defined as the technical leader who multiplies the output of the entire data organization — not just another senior engineer but the person who sets the technical standard that everyone else builds toward
0-to-1 Impact: Building the first reliable, automated production ML pipelines in a health and wellness platform operating at NYSE-listed scale — the type of architectural ownership that defines the career highlight reel of genuinely exceptional ML engineers
Health Tech Mission: Applying ML to problems that genuinely improve people’s health outcomes — churn prediction that keeps patients engaged with their care, LTV modeling that makes personalized healthcare accessible, supply chain optimization that ensures treatments reach patients reliably
Equity Upside: Meaningful equity in a NYSE-listed health tech company (HIMS) with genuine long-term value creation potential alongside a competitive £95K–£115K base salary
Position Overview
This Staff Data Scientist role at Hims & Hers in London is a full-time, hybrid senior technical leadership position within the Analytics & Data Science department. As a Staff Data Scientist, you are defined not simply as a strong individual contributor but as a force multiplier — the technical leader who identifies which problems are worth solving, simplifies ambiguous problems into executable paths, architects the ML foundations that the entire data organization builds upon, translates business strategy into production-ready machine learning systems, and elevates the technical bar through mentorship and standards-setting. You will lead the design and implementation of automated ML systems from 0 to 1, translate ambiguous business questions into concrete technical roadmaps, lead end-to-end deployment of ML products, partner across Engineering, Product, and Business, define model development standards, take full accountability for the complete model lifecycle from data design through long-term production performance, and actively mentor senior and mid-level Data Scientists. The role requires 8+ years of Data Science or ML Engineering experience, expert Python and SQL proficiency, production ML framework expertise (PyTorch, XGBoost, or LightGBM), and strong MLOps and cloud infrastructure capability (AWS or GCP).
Why This Hims & Hers Staff Data Scientist Role in London Is the Health Tech ML Career of 2026: Staff-level Data Scientists who combine 8+ years of production ML system development experience with expert Python and SQL proficiency, PyTorch or XGBoost/LightGBM framework mastery, end-to-end MLOps experience in AWS or GCP cloud environments, proven 0-to-1 ML pipeline architecture capability, and the leadership skills to influence without authority while mentoring a team of senior data scientists — represent the most rare, most commercially consequential, and most generously compensated data science talent profile in the London health technology market. Hims & Hers’ NYSE-listed scale, equity compensation, hybrid flexibility, and genuine health mission make this one of the most professionally fulfilling Staff DS roles available in the UK in 2026.
Key Responsibilities
0-to-1 ML Architecture — Foundation Building
- Architect and implement automated ML systems from the ground up — applying the pragmatic engineering judgment to make the right architectural choices (build vs. buy, simple vs. complex) that deliver technically sound, maintainable, and scalable ML infrastructure without over-engineering solutions that a growth-stage health tech company’s pace of iteration cannot sustain, writing production-grade code that establishes the ML infrastructure patterns and quality standards that the entire data organization can build upon
- Establish Hims & Hers’ core ML infrastructure — designing the model training pipelines, feature stores, experiment management frameworks, model deployment patterns, monitoring systems, and retraining workflows that transform the organization’s ML capability from exploratory notebook-based analysis into reliable, automated, production-grade ML systems that deliver consistent business value without requiring constant engineering intervention
- Balance technical correctness with delivery speed — applying the Staff-level engineering judgment that distinguishes pragmatic production ML architecture from both over-engineering and under-engineering, making deliberate architectural trade-off decisions that are explicitly communicated and documented, and building the ML foundation in a way that serves the organization’s immediate needs while remaining extensible as requirements evolve
Business Translation & Technical Roadmap Leadership
- Translate ambiguous business questions into concrete technical roadmaps — working with executives and business leaders across customer acquisition, churn dynamics, supply chain, and marketing to understand the business problems they are trying to solve, formulating clear problem statements, defining measurable success criteria, identifying the data and modelling approaches that will most efficiently deliver the required business impact, and producing the technical roadmaps that guide the data team’s execution priorities
- Identify which problems are worth solving — applying the business acumen and data science judgment that is the hallmark of Staff-level impact, proactively assessing the potential business value of different ML applications across Hims & Hers’ health and wellness platform, prioritizing the problems that will genuinely move the needle for customers and the business over those that appear technically interesting but deliver limited commercial value
- Partner across Engineering, Product, and Business to ensure technical strategy addresses the right business problems — maintaining the cross-functional relationships and organizational influence that ensure the data team’s ML roadmap remains tightly connected to Hims & Hers’ most important commercial priorities, preventing the technical isolation that can cause data science organizations to optimize for the wrong objectives
Production ML Deployment — End-to-End Ownership
- Lead the end-to-end deployment of ML products — taking complete technical ownership from initial data design and exploratory analysis through model development, validation, staging, production deployment, monitoring, and long-term performance management, ensuring that ML products are not just accurate in development but robust, maintainable, and fully integrated into Hims & Hers’ production infrastructure in ways that deliver reliable business value continuously
- Apply expert MLOps practices in cloud environments — using AWS or GCP infrastructure, CI/CD pipelines, model versioning, automated testing, deployment orchestration, and production monitoring frameworks to build the engineering discipline around ML deployment that ensures production ML systems behave predictably, fail gracefully, and are recoverable quickly when issues occur
- Own the full model lifecycle including long-term performance and business value — maintaining accountability for production ML systems after deployment, monitoring model performance against business KPIs, detecting model drift, managing retraining schedules, and proactively improving model quality in response to changes in data distributions, business requirements, or product strategy
Advanced ML Applications — Customer Behavior, Forecasting & Causal Inference
- Build customer behavior and propensity models — developing predictive models for churn prediction, propensity-to-buy scoring, lead scoring, and customer lifetime value (LTV) modeling that directly drive targeted marketing interventions, personalized product recommendations, and customer retention strategies across Hims & Hers’ health and wellness platform, applying the domain knowledge of health-specific customer behavior patterns that make these models genuinely actionable rather than technically impressive but commercially impractical
- Develop applied forecasting systems — building time-series forecasting models, anomaly detection systems, and non-stationary data handling approaches for demand and revenue planning use cases that give Hims & Hers’ supply chain and finance teams the forward-looking intelligence they need to plan inventory, allocate resources, and manage the operational complexity of a health product delivery business at scale
- Design and implement causal inference frameworks — going beyond standard A/B testing to design quasi-experimental methods, difference-in-differences analyses, and other causal inference approaches that measure true business impact in situations where randomized experiments are not feasible or sufficient, providing the executive-level evidence that justifies major product, marketing, and operational decisions
- Build optimization engines for marketing spend, inventory management, and resource allocation — developing the mathematical optimization models and heuristic search approaches that enable Hims & Hers to allocate its marketing budget, inventory investment, and operational resources across channels, markets, and products in ways that maximize measurable business outcomes subject to real operational constraints
Technical Standards, Mentorship & Organizational Force Multiplication
- Define and establish technical standards for model development across the data organization — creating the design document templates, peer review processes, model validation standards, code quality expectations, and documentation requirements that ensure ML work is reproducible, well-tested, correctly integrated with data and analytics engineering infrastructure, and built to the quality level that production health tech systems demand
- Actively mentor Senior and Mid-level Data Scientists — providing substantive technical guidance, peer code review, career development coaching, and the professional mentorship that elevates the technical capabilities of Hims & Hers’ broader data science team, fostering the culture of continuous learning and rigorous technical practice that defines high-performing data science organizations
- Act as a force multiplier for the data organization — leveraging personal technical expertise, organizational influence, and mentorship investment to produce exponential rather than linear impact on the data team’s collective output quality, velocity, and business impact, shaping how dozens of data professionals approach ML problems through standards, frameworks, and culture rather than through direct individual contribution alone
Qualifications & Requirements
Required Experience (8+ Years)
- 8+ years of professional experience in Data Science or ML Engineering — with a demonstrated track record of building and deploying production ML systems that delivered quantifiable business impact across customer acquisition, retention, supply chain, or marketing optimization use cases
- Expert Python and SQL proficiency — with the ability to write clean, tested, production-grade data science code rather than just exploratory notebook code, and to query and transform large-scale data from enterprise data warehouses
- Production ML framework expertise — in PyTorch, XGBoost, LightGBM, or comparable frameworks, with demonstrated experience training, validating, and deploying models in production cloud environments
- MLOps and engineering rigor — CI/CD experience, model lifecycle management, cloud infrastructure (AWS or GCP), and the software engineering discipline that distinguishes production ML from research ML
About Hims & Hers & Health Tech Data Science in 2026
Hims & Hers occupies a genuinely distinctive position in the global health technology landscape — a NYSE-listed consumer health company that has made the bold bet that making healthcare affordable, accessible, and personal at scale is not just a mission worth pursuing but a business model worth building around. For data scientists, this mission creates an ML application environment that is simultaneously commercially consequential and personally meaningful — where churn models keep patients connected to treatments that improve their lives, LTV models enable the customer acquisition investments that bring better healthcare to people who previously lacked access, and supply chain forecasting ensures that health products reach patients when they need them. Building the ML infrastructure that makes this mission operate more intelligently and more efficiently is the specific mandate of the Staff Data Scientist role — and London’s position as one of the world’s premier health technology and data science talent markets makes it the right place to build this capability. For data scientists with the experience, technical depth, and leadership ambition that the Staff designation demands, this role represents a rare combination of technical challenge, mission alignment, equity upside, and career advancement in the London health tech market in 2026.
Your Career Trajectory: Staff Data Scientist → Principal Data Scientist → Director of Data Science → VP Data Science → Chief Data Officer — a globally recognized, technically distinguished, and commercially impactful data science leadership career path built at the frontier of health technology and production machine learning.
Who Should Apply?
- Staff / Principal Data Scientists (8+ Years — UK Based): With proven production ML system delivery at scale, expert Python and ML framework proficiency, and the technical leadership capability to serve as an organizational force multiplier in a NYSE-listed health tech company
- Senior ML Engineers — Health Tech or DTC Focus: With 0-to-1 ML pipeline architecture experience at consumer health, digital health, or direct-to-consumer tech companies who want to advance to Staff level at Hims & Hers’ London Analytics team
- Data Scientists — LTV / Churn / Propensity Specialists: With expert customer behavior modeling experience — lifetime value, churn prediction, propensity-to-buy — who want to apply these skills at NYSE-listed scale in a mission-driven health and wellness platform
- Causal Inference & Experimentation Leaders: With quasi-experimental design, difference-in-differences, or advanced experimentation methodology expertise who want to build the causal inference capability that moves Hims & Hers beyond standard A/B testing
- UAE-Based Data Scientists — London Relocation: Experienced ML engineers currently in the UAE or MENA who want to advance to Staff level in London’s vibrant health technology market at a globally recognized, NYSE-listed health and wellness company with competitive equity compensation
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