Head of Data Science (Principal Data Scientist)

This is an exciting opportunity provide technical and strategic leadership for a new enterprise data science function. The function will own the full health data science lifecycle from problem to solution and is responsible for delivering pilots that aim to produce measurable improvements in clinical and operational KPIs, such as improving patient flow and discharge, and improving quality of care. The role will directly report to senior leadership, focused on supporting the most pressing objectives for the Trust. The post-holder will build and manage a focused, high-calibre team of data scientists. Essential Criteria: Higher degree (Masters or PhD) in data-science related field Strong healthcare / clinical domain knowledge Senior data science leadership experience, with a track record of delivery Hands-on expertise in Python, SQL, and modern ML and statistical methods Experience owning the full data science lifecycle Experience building, leading, and developing high-calibre technical teams Excellent communication skills across technical and non-technical audiences, including at senior level Desirable Criteria: Data science delivery in consultancy or other industry setting Medical degree or other clinical experience Experience building and deploying solutions in cloud data platforms Lead the enterprise data science function at GSTT, setting strategy and prioritising problems across clinical and operational pathways where data science can deliver measurable improvement. Own the end-to-end pathway, including discovery, requirements engineering, solutions development, deployment, experimentation, testing, and evaluation. Act as senior hands-on contributor, owning the team's code and analytical output. Hold the function accountable for outcomes (movement in target KPIs), not intermediate outputs such as dashboards, reports, or deployed models - confirming benefit before scaling, iterating, or stopping. Provide technical expertise in data science and machine learning (statistical and predictive modelling, LLMs, causal inference), ensuring fit-for-purpose solutions where a model is one option among several. Build scalable frameworks for productionising pilots and monitoring the impact and safety of deployed decision-support tools, in partnership with data engineering. Engage a broad range of stakeholders - executive, clinical, and operational leaders, ICBs, patients, and technology partners - to align initiatives with GSTT and wider NHS priorities. Embed fairness into evaluation, reporting on how decision insights affect healthcare inequalities and differential outcomes for marginalised groups. Develop the data science workforce, recruiting expert talent, upskilling existing analysts, and managing team appraisals and career development. AI Centre for Value-Based Healthcare The AI, Data \& Digital Innovation directorate is made up of data and technology experts - based in GSTT but working closely as a team with KCH and KCL. The team forms part of the Artificial Intelligence Centre for Value-Based Healthcare - a consortium of NHS, academic, and industry partners from across the UK. This consortium offers expert professional technical delivery across data engineering, data science \& AI development, and software engineering. Programmes include region-wide infrastructure delivery of cloud and federated platforms, multi-modal Real-World Data engineering, foundation model development, and development of different Language AI solutions. London / GSTT Snowflake Platform A secure data and research cloud platform that provides access to some of the broadest and deepest data in the NHS, including low latency patient-level data flows from primary care, linked to Acute Trust data. The platform also supports data science and deployment of advanced analytics and machine learning solutions, including Language AI for unstructured data extraction. Strategic leadership The postholder is responsible for setting the direction for data science at GSTT, deciding which clinical and operational challenges to tackle based on where measurable value can be created and how well they map to Trust-wide goals. This involves working closely with a wide network of partners, from executives and clinicians to Integrated Care Boards, patients, and technology suppliers. so that the function's work stays relevant to GSTT's changing needs and, as tools spread more widely, to national aims around efficiency, productivity, and care quality. Operational leadership As a working team lead, the postholder both manages and personally contributes to delivery, guiding pilots through every stage from framing the problem to measuring results. They keep the team focused on strategic priorities and on the outcomes that matter rather than intermediate deliverables, distribute internal and partner resources sensibly by starting small and expanding what proves effective, and apply disciplined product management and rapid test-and-learn cycles while owning project risk. Technical leadership The postholder will be expected to bring practical, hands-on skill across data science and machine learning, spanning statistical and predictive methods, LLMs, causal inference and experimental methods, and bespoke workflows. Develops sustainable ways to move pilots into production alongside data engineering, and offers technical direction to related work, including academic and industry collaborations.