Lead Data Scientist - Healthcare in London

Lead Data Scientist - Healthcare in London

London Full-Time 43200 - 72000 £ / year (est.) No working from home possible
Kainos Group plc

At a Glance

  • Tasks: Lead the design and delivery of advanced AI solutions in healthcare.
  • Company: Join Kainos, a leading AI and data business with a people-first culture.
  • Benefits: Enjoy competitive salary, remote work options, and professional development opportunities.
  • Other info: Be part of a diverse team that values innovation and continuous learning.
  • Why this job: Make a real impact in healthcare by leveraging cutting-edge AI technologies.
  • Qualifications: Degree in Computer Science or related field; strong AI/ML skills required.

The predicted salary is between 43200 - 72000 £ per year.

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.

JOB PROFILE DESCRIPTION

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.

MAIN PURPOSE OF THE ROLE & RESPONSIBILITIES IN THE BUSINESS:

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.

MINIMUM (ESSENTIAL) 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.
  • 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.

Embracing our differences

At Kainos, we believe in the power of diversity, equity and inclusion. We are committed to building a team that is as diverse as the world we live in, where everyone is valued, respected, and given an equal chance to thrive. We actively seek out talented people from all backgrounds, regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other characteristic that makes them who they are. We also believe every candidate deserves a level playing field. Our friendly talent acquisition team is here to support you every step of the way, so if you require any accommodations or adjustments, we encourage you to reach out. We understand that everyone's journey is different, and by having a private conversation we can ensure that our recruitment process is tailored to your needs.

At Kainos we use technology to solve real problems for our customers, overcome big challenges for businesses, and make people's lives easier. We build strong relationships with our customers and go beyond to change the way they work today and the impact they have tomorrow. Our two specialist practices, Digital Services and Workday, work globally for clients across healthcare, commercial and the public sector to make the world a little bit better, day by day. Our people love the exciting work, the cutting-edge technologies and the benefits we offer. That's why we've been ranked in the Sunday Times Top 100 Best Companies on numerous occasions.

Lead Data Scientist - Healthcare in London employer: Kainos Group plc

At Kainos, we pride ourselves on fostering a people-first culture that champions innovation and collaboration. As a Lead Data Scientist in the healthcare sector, you'll not only work with cutting-edge AI technologies but also enjoy ample opportunities for professional growth and development within a diverse and ambitious team. Our commitment to ethical AI practices and employee well-being makes Kainos an exceptional place to build a meaningful career.

Kainos Group plc

Contact Details:

Kainos Group plc Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Data Scientist - Healthcare in London

Tip Number 1

Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Lead Data Scientist role.

Tip Number 2

Show off your skills! Create a portfolio showcasing your AI projects, especially those related to healthcare. This will give potential employers a taste of what you can bring to the table.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with clients and team members.

Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our mission at Kainos.

We think you need these skills to ace Lead Data Scientist - Healthcare in London

Machine Learning
Generative AI
Agentic AI
Python
AI Engineering Approaches
Prompt Engineering
Retrieval-Augmented Generation (RAG)

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with AI/ML models and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how you can contribute to our mission at Kainos. Keep it engaging and personal – we love to see your personality come through.

Showcase Your Technical Skills:Don’t forget to mention your technical expertise, especially in Python and AI frameworks. We’re keen on seeing your hands-on experience, so include specific examples of how you've applied these skills in real-world scenarios.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you’re genuinely interested in joining our team!

How to prepare for a job interview at Kainos Group plc

Know Your AI Stuff

Make sure you brush up on your knowledge of AI and machine learning models, especially the ones mentioned in the job description. Be ready to discuss your experience with supervised/unsupervised learning, reinforcement learning, and any specific frameworks like PyTorch or TensorFlow.

Showcase Your Leadership Skills

As a Lead Data Scientist, you'll need to demonstrate your ability to manage and mentor a team. Prepare examples of how you've coached junior members in the past and how you foster a culture of innovation and continuous learning.

Communicate Clearly

Since you'll be translating complex technical concepts into non-technical language for clients, practice explaining your past projects in simple terms. This will show that you can bridge the gap between technical and non-technical stakeholders effectively.

Emphasise Responsible AI Practices

Kainos values responsible AI, so be prepared to discuss ethical considerations and model interpretability. Share your thoughts on how to implement responsible AI practices in your work and any relevant experiences you've had in this area.