Lead Data Scientist - Healthcare

Kainos
City of London
2 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Engineer

Lead Data Analyst

Data Scientist

Join to apply for the Lead Data Scientist - Healthcare role at Kainos.


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.


Main Purpose of the Role & Responsibilities

As a Lead Data Scientist, you will architect, design and deliver advanced AI solutions using state‑of‑the‑art machine learning, generative and agentic AI technologies. You’ll champion modern AI frameworks, AIOps best practices and scalable cloud‑native architectures. The role involves hands‑on technical leadership and collaboration with customers to translate business challenges into trustworthy AI solutions, ensuring responsible AI practices throughout. You will mentor a small team, manage performance, and provide strategic direction while solving complex problems.


Minimum (essential) Requirements

  • A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or a similar quantitative field.
  • Deep understanding and experience developing 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 translate requirements into non‑technical language.
  • Experience managing, coaching and developing junior team members and the 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), and ML libraries (e.g. scikit‑learn, XGBoost).
  • Experience with AI data storage, 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. If you require accommodations or adjustments, please reach out – we are happy to support you.


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.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.