Lead Data Scientist - Healthcare

Join Kainos and Shape the Future

At Kainos, we’re problem solvers, innovators, and collaborators - driven by a shared mission to create real impact. Whether we’re transforming digital services for millions, delivering cutting‑edge Workday solutions, or pushing the boundaries of technology, we do it together.

We believe in a people‑first culture, where your ideas are valued, your growth is supported, and your contributions truly make a difference. Here, you’ll be part of a diverse, ambitious team that celebrates creativity and collaboration.

Ready to make your mark?
Join us and be part of something bigger.

Kainos is recognised as one of the UK’s leading AI and data businesses, with a decade-long track record of delivering impactful, production‑grade AI solutions for clients across government, healthcare, defence, and commercial sectors. Kainos is at the forefront of AI innovation, trusted by Microsoft, AWS, and others to deliver advanced AI and data solutions at citizen scale.

Our 150‑strong AI and Data Practice brings together deep expertise in machine learning, generative AI, agentic AI and data. We are pioneers in responsible AI, having authored the UK government’s AI Cyber Security Code of Practice implementation guide and we partner with leading organisations to ensure AI is deployed ethically, securely and with measurable business value. Our teams are at the cutting edge of AI research and delivery;

it is truly an exciting team to join Kainos as we further grow our AI capability.

As a Lead Data Scientist at Kainos, you will architect, design, and deliver advanced AI solutions leveraging state‑of‑the‑art machine learning, generative and agentic AI technologies. You will drive the adoption of modern AI frameworks, AIOps best practices and scalable cloud‑native architectures. Your role will involve hands‑on technical leadership, collaborating with customers to translate business challenges into trustworthy AI solutions and ensuring responsible AI practices throughout.

As a technical mentor, you will foster a culture of innovation, continuous learning, and engineering excellence.

It is a fast‑paced environment, so it is important for you to make sound, reasoned decisions. You will do this whilst learning about new technologies and approaches, with talented colleagues that will help you to develop and grow. You will manage, coach, and develop a small number of staff, with a focus on managing employee performance and assisting in their career development.

You will also provide direction and leadership for your team as you solve challenging problems together.

• A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or a similar quantitative field.
• Have a deep understanding and developing of AI/ML models, including time series, supervised/unsupervised learning, reinforcement learning and LLMs.
• Experience with the latest AI engineering approaches such as prompt engineering, retrieval‑augmented generation (RAG), and agentic AI.
• Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc).
• Expertise in data engineering for AI: handling large‑scale, unstructured, and multimodal data.
• Understanding of responsible AI principles, model interpretability, and ethical considerations.
• Strong interpersonal skills with the ability to lead client projects and establish requirements in non‑technical language.
• We are passionate about developing people, you will bring experience in managing, coaching, and developing junior members of a team and wider community.

• Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, Tensor Flow), fine‑tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit‑learn, XGBoost).
• Experience with data storage for AI, vector databases, semantic search, and knowledge graphs.
• Contributions to open‑source AI projects or research publications.
• Familiarity with AI security, privacy, and compliance standards e.g. ISO
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