Job Opportunities API

Do you want to apply data science to one of the most important challenges in health research: enabling safe use of sensitive data at scale?   In this role, you’ll develop privacy and security controls that protect participants while helping researchers generate insights faster and more safely.  Our Future Health is an ambitious collaboration between the public, charity and private sectors, designed to help people live healthier lives for longer through better prevention, earlier detection and improved treatment of diseases. We will speed up the discovery of new methods of early disease detection, and the evaluation of new diagnostic tools, to help identify and treat diseases early, when outcomes are usually better. With over 2.5M volunteers across the UK, we’re now the world’s biggest health research programme of its kind, and our volunteer group is also more diverse than other, similar health research programmes. Technology and data are central to our mission. Our systems power web sites, clinics across the UK, secure analytics and research systems, pipelines that process highly sensitive health and genetic data, and we are continuing to grow our data science capability to support this ambition. To realise our ambition safely, we need to continue developing world-class approaches to data privacy, data security and responsible access to health data. We are looking for a Senior Data Scientist specialising in privacy, security and risk modelling , to help design, build and scale data-driven controls that protect participants while enabling cutting-edge research.  This is a hands-on role where you’ll apply strong data science skills and an engineering mindset to real operational problems: safe outputs review, re-identification risk, privacy risks in trained models, synthetic data, and data-driven security controls. You will work closely with teams across Product, Security, Engineering, Science, Data Protection, and Researcher Operations as well as external experts to develop practical, scalable and evidence-based solutions.  You will be expected to work closely with users of these systems including researchers, Airlock reviewers, access governance reviewers and security specialists, to understand their workflows, pain points and risk decisions. A key part of the role will be turning complex privacy and security problems into trusted algorithms, evidence and automated support.  What you’ll do  Develop data-driven approaches to disclosure control and safe outputs review, supporting the scaling of our TRE (Trusted Research Environment) Airlock. This may include building algorithms and automated review tools to classify outputs, detect potentially disclosive content, identify patterns of risk, and provide explainable decision support for human reviewers.  Work directly with Airlock reviewers and operational users to understand where automation can help, where human judgement is essential, and how tools should be designed to support consistent, auditable and proportionate decisions.  Contribute to our approach to de-identification and re-identification risk assessment, helping us assess how privacy risk changes across datasets, access models and analytical outputs.  Help us develop our approaches to safe AI using health data, including how we assess and manage privacy risks associated with trained models.  Explore and develop approaches to synthetic data generation, assessing how synthetic data can be used safely and usefully, and how to evaluate the privacy, fidelity and utility trade-offs of different approaches.  Collaborate with our Information Security team on data-driven security contro