Lead Data Scientist - Healthcare
Role details
Job location
Tech stack
Job description
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.
Requirements
- A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or in 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.
Desirable
- Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), 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. ISO42001.