Principal Data Scientist - Healthcare

Kainos
Belfast
2 months ago
Create job alert

JOB DESCRIPTION

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-longtrack recordof 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 Practicebringstogether deepexpertisein machine learning, generative AI, agenticAIand 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 thecutting edgeof 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:

AsaPrincipal Data Scientist at Kainos, you will be accountable for the successful delivery of large-scale, high-impact AI solutions thatleveragestate-of-the-artmachine learning, generative, and agentic AI technologies. You willhelpset the direction for AI and data science across the business, driving the adoption of modern AI development practices and scalable, cloud-native architectures at enterprise scale.You will provide technical and thought leadership, engaging with C-level and senior stakeholders to define architectural principlesandstrategic direction. Asasenior technical leader in AI, you will foster a culture of innovation, continuouslearningand engineering excellence—both within Kainos and across the wider industry.

You will lead, mentor, and develop a community of data scientists, AI engineers, and technical managers, ensuring the adoption of robust standards and responsible AI practices. You will build enduring customer relationships, proactively develop new alliances with technology partnersand shape Kainos’ commercial AI offerings. Your leadership will be instrumental in embedding commercial acumen, influencing accountstrategiesand ensuringcustomers getmeasurable business value from AI investments.

MINIMUM(ESSENTIAL)REQUIREMENTS:

Proventrack recordof accountability for the delivery of complex, production-grade AI/ML solutions at scale.

Demonstrable experienceoftechnical leadershipinAI delivery.

Deepexpertisein developing and assuring advanced AI/ML models, including time series, supervised/unsupervised learning, reinforcement learning, LLMsand agentic AI.

Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG)and orchestration of agentic AI systems.

Expertisein data engineering for AI: handling large-scale, unstructured, and multimodal data, and integrating non-traditional data sources.

Deep understanding of responsible AI principles, modelinterpretabilityand ethical considerations, witha track recordof influencing policy and standards.

Ability to communicate and negotiate with C-level and senior stakeholders, translating complex technical concepts into business value.

Experience in developing and executing account strategies, shaping commercial AIofferingsand driving business development in partnership with sales and account managers.

Demonstrated ability to build andleadhigh-performing teamsand widerAI and data science communities.

Strong commercial acumen with a history of influencing the commercial success of AI products and solutions.

DESIRABLE:

Experience with modern deep learning frameworks (e.g.PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g.scikit-learn,XGBoost).

Experience with data storage for AI, vector databases, semantic search, and knowledge graphs.

Active contribution to open-source AI projects, research publications, and industry events/websites.

Familiarity with AI security, privacy, and compliance standards (e.g.ISO 42001).

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.

Related Jobs

View all jobs

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist London, United Kingdom

Principal Data Scientist: ML Leader, Mentor, Hybrid Role

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.