At a Glance
- Tasks: Lead a data science squad to create impactful commercial recommendations and personalised patient experiences.
- Company: Eucalyptus, a fast-growing digital healthcare company transforming weight management.
- Benefits: Flexible hybrid work, wellness allowance, personal development budget, and 25 days holiday.
- Why this job: Make a real difference in patients' lives while advancing your career in a dynamic environment.
- Qualifications: 8+ years in data science with experience in recommendation systems and team leadership.
- Other info: Join a passionate team dedicated to innovation and patient care.
The predicted salary is between 48000 - 72000 £ per year.
More than 1 billion people globally live with obesity, a significant leading indicator of many preventable chronic diseases such as diabetes and heart disease. Eucalyptus is the company behind Juniper, one of the world's largest weight management programs combining GLP-1 medication with a tailored nutrition and exercise programme, supported by our multidisciplinary care team of prescribers, health coaches, dietitians, nurses and pharmacists. Our published clinical research demonstrates that our combined approach to weight management and lifestyle change increases the likelihood of our patients losing significant weight during their treatment with Juniper by four times.
Since launching, we’ve grown fast to support millions of patients. In the last 12 months:
- We grew the size of our patient base by 10x in the UK.
- Received selective NICE endorsement for our holistic approach to obesity management.
- Grew our team from 50 to 200.
Globally, we grew revenue by >120% YoY, while reducing cash burned by 90% YoY, with over $100M USD raised from global investors such as BOND, NewView, Blackbird and Airtree - early backers of companies like Canva, Stripe, Uber and Airbnb.
What’s next? In 2025, we are charting the path to support hundreds of thousands of patients while launching into new conditions, demographics, and geographies as we move towards our vision of creating a preventive healthcare ecosystem. We’re building the world’s largest international digital healthcare company. This will be highly challenging, very rewarding and the adventure of a lifetime, working with the best operators you will ever encounter. If that gets you excited, let’s talk!
About the role: We’re hiring a Data Science Lead to build and lead a commercial & transactional data science squad in the UK. This role sits at the intersection of product, data science, and engineering, with a primary focus on designing and delivering recommendations that drive:
- Product discovery and cross-sell (OTC, programs, prescriptions)
- Personalised patient experiences
- Commercial outcomes that align with patient value
This is a hands-on role with early people leadership responsibilities. You’ll be responsible for shaping the technical direction of the squad, delivering models into production, and working closely with product and engineering partners to ensure real-world impact.
What you’ll do: In this role, you’ll balance technical leadership and hands-on delivery — setting the vision for how data science is applied to our commercial ecosystem in the business. You’ll ensure the team’s work is impactful, reliable, and aligned with organisational priorities.
- Build and lead a small data science squad focused on transactional and commercial recommendation systems across OTC products, structured programs, and prescription cross-sell.
- Design, experiment with, and iterate on recommendation models, starting with lightweight heuristics to get early signal and scaling sophistication where clear upside exists.
- Translate product and commercial goals into concrete data science roadmaps, aligning experimentation, feature development, and delivery timelines.
- Partner closely with product and engineering teams, influencing technical direction without being prescriptive and ensuring solutions are practical, scalable, and valuable to patients.
- Support production-ready data science, including feature definition, evaluation design, model handover, monitoring, and iteration in collaboration with ML and data engineering.
- Set technical standards and best practices for experimentation, model evaluation, and deployment within the squad.
About you (Who you are): We’re looking for someone who is strong technically, commercially minded, and comfortable operating in ambiguity. You likely have:
- 8+ years’ experience in data science, applied ML, or advanced analytics including prior experience leading either technically or direct people management.
- Experience building and iterating on recommendation, ranking, or personalisation systems.
- Strong foundations in statistics, machine learning, feature engineering, and model evaluation.
- Hands-on experience with Python, SQL, and modern ML libraries.
- Exposure to production ML environments and collaboration with ML/data engineering teams.
- The ability to clearly communicate technical ideas to product and non-technical stakeholders.
- An opinionated but pragmatic approach to how data science should be built and deployed.
- Prior people leadership experience is a plus, but not required — stepping into squad-level leadership while remaining deeply technical.
Why you should join Euc: Make real impact, fast – We build in the open together, which helps us learn and iterate more quickly so we can deliver high quality outcomes faster than anyone else. Helping impact patients lives for the better from the moment you join Euc.
You’ll be supported to accelerate your career – Regular feedback alongside our bi-annual performance reviews, a professional development budget & leave help ensure you have the support you need to level up. We’re committed to helping every Eucalypt reach their full potential.
You’ll work with others who are incredibly passionate about what they do – Our talent bar is high and our work ethic is strong. You’ll get to stretch yourself every day, be given autonomy to tackle interesting problems, and work amongst people who care deeply about our patients.
We also offer a range of benefits including:
- Your own stake in the business with our employee options program.
- Newly opened HQ in vibrant Old Street, designed for focus and collaboration.
- A flexible hybrid setup: 3 days a week in our Old Street office.
- A monthly wellness allowance, for you to spend on whatever wellness means to you.
- A yearly personal development budget and 3 extra days of leave to continuously up-skill yourself.
- 25 days holiday + bank holidays with an enhanced parental leave policy.
- A fun office with regular socials including after school sport, clubs, cycle kick offs and seasonal parties.
At Eucalyptus, we value individuals from all backgrounds, experiences, and perspectives, and we embrace the unique qualities each person brings. When you apply, please let us know of any reasonable adjustments you may need during the interview process.
Data Science Lead, UK in London employer: Eucalyptus
Contact Detail:
Eucalyptus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Lead, UK in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions and scenarios related to data science. Use the STAR method (Situation, Task, Action, Result) to structure your answers and showcase your problem-solving skills effectively.
✨Tip Number 3
Showcase your passion for the role! During interviews, share your thoughts on the latest trends in data science and how they could apply to Eucalyptus. This will demonstrate your enthusiasm and knowledge about the field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Eucalyptus.
We think you need these skills to ace Data Science Lead, UK in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Science Lead role. Highlight your relevant experience in data science, especially around recommendation systems, and show how it aligns with our mission at Eucalyptus.
Showcase Your Technical Skills: We want to see your hands-on experience with Python, SQL, and ML libraries. Include specific projects or achievements that demonstrate your technical prowess and how you've applied these skills in real-world scenarios.
Communicate Clearly: Remember, you’ll be working with both technical and non-technical teams. Use clear, straightforward language in your application to explain complex ideas, showing us you can bridge the gap between data science and product development.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to make a real impact in healthcare.
How to prepare for a job interview at Eucalyptus
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around recommendation systems and machine learning. Be ready to discuss your past projects and how you've applied these concepts in real-world scenarios.
✨Understand the Company’s Mission
Familiarise yourself with Eucalyptus and their approach to weight management. Knowing their mission and how data science plays a role in improving patient outcomes will show your genuine interest and alignment with their goals.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions. Prepare to explain your thought process behind model selection, feature engineering, and evaluation metrics. Practising coding problems in Python or SQL can also give you an edge.
✨Show Your Leadership Potential
Even if you haven't held a formal leadership role, think of examples where you've influenced others or led a project. Highlight your ability to communicate complex ideas clearly to both technical and non-technical stakeholders.