Data Science Manager

We’re working with a market-leading health-focused organisation that’s using cutting-edge data science and AI to reshape how people access and experience healthcare. They’ve built a strong data science function that’s now growing again—this time with a key leadership role.
 
What you’ll be doing:
They’re looking for a Data Science Manager to lead a small but strong team across a range of live and upcoming projects spanning traditional AI, GenAI and machine learning. The environment is genuinely collaborative, with a healthy investment in tools, learning, and innovation. This role offers the rare opportunity to stay hands-on with the tech while also stepping into a strategic leadership position with strong support from above.
 
You’ll be responsible for managing and mentoring a team of four data scientists working on complex data challenges with real-world impact. You’ll be involved in projects across multiple domains—ranging from pricing optimisation and claims management to customer behaviour modelling and new GenAI initiatives.
 
Day to day, you’ll split your time between technical delivery, people leadership, and cross-functional collaboration. You’ll be the person who can understand the scientific complexity but communicate its value clearly to non-technical stakeholders, helping drive commercial outcomes from data insights. The role will report into an experienced leader who’s happy to give you room to lead while offering support as needed.
 
There’s also a strong emphasis on upskilling and internal learning. Think regular hackathons, dedicated learning time (two hours every week), and a real culture of investing in the team.
 
What experience you’ll need to apply:

• Currently working as a Data Science Manager, Lead Data Scientist or similar
• Proven experience leading or mentoring data scientists within a commercial environment
• Experience working on GenAI/MLOps and similar projects
• Solid background delivering AI/ML projects end-to-end, with real business impact
• Hands-on Python skills including libraries like Scikit-learn, TensorFlow, Keras, and PySpark
• Strong understanding of model deployment and MLOps best practices
• Ability to work with real-world, unbalanced and messy datasets
• Skilled in translating technical work into insights for non-technical stakeholders
• Experience working across cross-functional teams (engineers, architects, analysts)
• Sector experience in healthcare, finance or insurance is beneficial but not essential

 
What you’ll get in return:

• Up to £90,000 basic salary depending on experience
• Annual bonus linked to company and personal performance
• Great pension, life assurance and more!
• Hybrid working – typically 2–3 days per week

 
What’s next?
Apply with your updated CV and we’ll be in touch to talk through the opportunity in more detail. Any questions in the meantime? Drop Tegan a message – happy to chat it through!