Staff Data Scientist in London

Staff Data Scientist in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead the design and implementation of innovative machine learning systems to enhance healthcare.
  • Company: Join Hims & Hers, a pioneering health and wellness platform focused on personalised care.
  • Benefits: Enjoy flexible remote work, competitive salary, and a culture that prioritises wellness and diversity.
  • Other info: Be part of a diverse team committed to continuous learning and ethical practices.
  • Why this job: Make a real impact in healthcare by solving complex problems with cutting-edge technology.
  • Qualifications: 8+ years in Data Science or ML Engineering, with strong Python and SQL skills.

The predicted salary is between 63000 - 77000 £ per year.

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve.

About the Role: As a Staff Data Scientist at Hims & Hers, you are a technical leader and a "force multiplier" for our data organization. You do not just solve the most difficult problems; you identify which problems are worth solving to move the needle for our customers. You will serve as a technical anchor, simplifying ambiguous problems into executable paths for the team.

In this role, you will bridge the gap between business strategy and production-ready machine learning. Whether you are building frameworks for growth, optimizing our supply chain, or refining marketing attribution, you will ensure our data products are technically sound, scalable, and built to deliver measurable business results.

You Will:

  • Architect the 0-to-1 Foundation: Lead the design and implementation of automated ML systems. You know how to balance "doing it right" with "doing it fast," making pragmatic architectural choices (build vs. buy, simple vs. complex) while rolling up your sleeves to write production code and establish our core ML infrastructure.
  • Translate Business Needs: Turn ambiguous business questions (from customer acquisition to churn dynamics) into concrete technical roadmaps that deliver clear, actionable results.
  • Drive Execution and Reliability: Lead the end-to-end deployment of ML products, ensuring they are not just accurate but robust, maintainable, and fully integrated into our production infrastructure.
  • Connect Technical & Business Goals: Partner across Engineering, Product, and Business to ensure our technical strategy is solving the right business problems and moving our core metrics.
  • Define Technical Standards: Act as a force multiplier by establishing the standards for model development. You will lead design docs and peer reviews that ensure our work is reproducible and integrates with the work of our Data and Analytics Engineering partners.
  • Own the Results: Take accountability for the full model lifecycle, from the initial data design through to the long-term performance and business value of production systems.
  • Mentorship & Coaching: Actively mentor Senior and Mid-level Data Scientists, elevating the technical bar and fostering a culture of continuous learning across the data organization.

Experience & Skills:

  • 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).
  • 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.
  • Leadership & Influence: Proven ability to influence without authority. You can translate complex technical logic into compelling narratives for executive leadership.
  • Engineering Rigor: Experience with CI/CD, ML Ops, and managing the full lifecycle of models in a cloud-based production environment (AWS or GCP).
  • Education: BS, MS, or PhD in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.) or equivalent field expertise.

Preferred Qualifications:

  • 0-to-1 Execution: Experience taking the very first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines.
  • Advanced Business ML (Experience in 1-2 of the following):
    • 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.
    • 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.
    • Causal Inference: Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing.

We are committed to building a workforce that reflects diverse perspectives and prioritises ethics, wellness, and a strong sense of belonging. 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.

Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws.

Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at accommodations@forhims.com and describe the needed accommodation.

Staff Data Scientist in London employer: hims & hers

Hims & Hers is an exceptional employer that prioritises the well-being and safety of its employees, particularly in the dynamic environment of our Fulfillment Center in the UK. With a strong commitment to fostering a positive work culture, we offer comprehensive benefits, opportunities for professional growth, and a collaborative atmosphere where your contributions to safety and compliance are valued and recognised.

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Contact Details:

hims & hers Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Data Scientist in London

Get Involved in Data Science Meetups

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Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Staff Data Scientist at hims & hers.

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like hims & hers.

Apply Directly through Our Website

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We think you need these skills to ace Staff Data Scientist in London

Python
SQL
Machine Learning
Data Science
ML Frameworks (e.g., PyTorch, XGBoost, LightGBM)
CI/CD
ML Ops

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at hims & hers, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at hims & hers. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at hims & hers

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at hims & hers!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.