Data Science & AI Graduate

We are seeking an exceptional graduate to join Stalis as a generalist across our technical and operational functions. You will work closely with teams across the business, developing a deep understanding of how healthcare data moves through our systems and identifying opportunities to apply programming, modern tooling, and AI to improve how we work. Over time, as Stalis’s data intelligence capability matures, you will have the opportunity to contribute directly to machine learning and analytics work that shapes our next generation of products.

This is a broad role, and not every task will be glamorous. Much of the early value comes from genuinely understanding how work is done at Stalis today - which means doing the work, not just observing it. Some of your time will be spent on detailed, careful data tasks that are essential to our clients. The opportunity is to use that understanding as the foundation for automation, improvement, and new capability. The best ideas will come from the ground up, and we expect you to find them.

•         Work alongside our data migration and engineering teams on live client projects, contributing to the day-to-day delivery of healthcare data work.

•         Identify inefficiencies, repetitive tasks, and fragile processes - and build the scripts, tools, and small systems that fix them.

•         Write and maintain code, primarily in Python & SQL, to automate workflows, process data, and support internal operations.

•         Apply and experiment with AI tooling - LLMs, embeddings, classifiers - to problems across the business where they add real value, and be honest about where they don’t.

•         Communicate your work clearly, in writing and in person, to colleagues who are not data scientists - so that your improvements get adopted rather than sidelined.

•         Over time, contribute to Stalis’s emerging data science and machine learning capability, including schema mapping, clinical data analytics, and data products.

You will need most, if not all, of the following:

•         Academic background. A strong degree from a top university in a quantitative or technical discipline - physics, engineering, computer science, mathematics, or similar.

•         Genuine technical aptitude. Comfortable writing code, and keen to write more of it. We are not looking for a particular stack or prior industry experience, but you should already be writing code for fun, coursework, or projects, and be able to pick up new tools quickly.

•         AI-savvy. Fluent with modern AI tools as a day-to-day part of how you work and think. You know what LLMs are good at, what they’re bad at, and how to use them without being credulous about their output.

•         Self-directed. You find problems, scope them yourself, and take them to a useful end state without being spoon-fed tasks. You are comfortable operating under ambiguity and choosing what to work on when it isn’t obvious.

•         Discerning and pragmatic. You can tell the difference between a problem worth solving properly and one worth a fifty-line script today. You don’t gold-plate.

•         Strong communicator, in writing especially. You can write a short memo or a handover document that brings people along. In a small, distributed business, this matters more than people think.

•         Emotionally intelligent. Improvements to how people work can feel like criticism, even when they aren’t. You can read a room, win people over, and work collaboratively with colleagues who know things you don’t.

•         Domain-humble. You are curious about how Stalis works today before you try to change it. You understand that experienced colleagues know things that aren’t written down, and you treat that knowledge as an asset.

•         Unusual breadth of exposure for a graduate role - you will see how a specialist healthcare data company actually runs, from the data up.

•         A path into machine learning and data science work as Stalis’s data intelligence capability develops, with real problems and real data to work on.

•         Direct access to senior colleagues, reporting to the Head of Data Science, and genuine influence over how the company evolves.

•         A role that will grow as quickly as you do.