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 Senior Data Scientist at Kainos, you will be building 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 delivery, 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 support your colleagues and more junior developers, providing direction support 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 and team working. 

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. 

• Actively contributes to open-source AI projects, research publications, and industry events/websites.  

• Familiarity with AI security, privacy, and compliance standards e.g. ISO42001.