Job at a glance
Designing, building and deploying machine learning models and AI solutions across the full lifecycle, from data preparation and model development through to deployment, monitoring and optimisation. Delivering actionable insights from complex healthcare and insurance datasets, presenting findings to stakeholders at all levels, including senior leadership. Leading projects from initial problem definition through to implementation and business adoption.
Building and maintaining robust MLOps frameworks, governance processes and best practices. Partnering with IT architects, platform teams and solution designers to ensure cloud environments support analytical and AI workloads. Conducting ad hoc analysis using large-scale datasets including claims, pre-authorisation and customer service data. Developing and maintaining strong stakeholder relationships across the business.
Coaching and mentoring junior team members and potentially supporting summer interns. Championing coding standards, quality assurance and analytical best practice. Working within Agile teams where appropriate. Ensuring all work complies with regulatory requirements and maintains the highest standards of data security and governance. Supporting the development of Generative AI solutions, including Retrieval-Augmented Generation (RAG), semantic search, agentic workflows and LLM orchestration.
Contributing thought leadership in Data Science, Machine Learning, AI and Generative AI to help position UK Insurance Data & Analytics as a centre of excellence. We're seeking a highly analytical and commercially minded professional with a passion for turning data into meaningful outcomes. Essential Skills and Experience Proven experience delivering end-to-end machine learning solutions, including model development, deployment, monitoring and continuous improvement.
Experience implementing MLOps frameworks and operationalising machine learning at scale. Strong track record of generating actionable insights from data, ideally within healthcare, insurance or another regulated industry. Hands-on expertise with supervised and unsupervised machine learning techniques, including: + XGBoost + LightGBM + Random Forests + Clustering techniques + Regression analysis + Correlation analysis + Multilevel modelling Strong programming and data engineering skills using Python, SQL and/or SAS.
Experience building automated machine learning pipelines and working with large enterprise data environments. Strong experience with the Microsoft Azure ecosystem, including: + Azure Machine Learning + Azure AI Studio + Azure Kubernetes Service (AKS) + MLOps and model monitoring capabilities Experience developing Generative AI solutions using Azure AI Foundry, OpenAI technologies or Google Vertex AI.
Excellent communication skills with the ability to influence and engage stakeholders at all levels. Demonstrated experience coaching, mentoring and developing colleagues. Experience working within Agile delivery environments, using tools such as Azure DevOps. Desirable Skills and Experience Experience with advanced Generative AI and Agentic AI solutions, including: + Retrieval-Augmented Generation (RAG) + Embeddings and vector search + Evaluation frameworks + LLM orchestration Hands-on experience with frameworks such as: + LangChain + LlamaIndex + CrewAI + AutoGen + Google ADK + Similar AI frameworks Bachelor's degree in Mathematics, Statistics, Computer Science or another quantitative discipline.
Master's degree in Data Science, Statistics, Epidemiology or a related field. About You You'll be someone who: Thrives on solving complex business problems using data. Can independently lead projects from concept through to implementation. Balances technical excellence with commercial impact. Communicates complex analytical concepts in a clear and engaging way. Builds strong relationships across technical and non-technical teams.
Enjoys mentoring and supporting the development of others. Has a genuine passion for th