Data Science Lead

As an experienced technical leader and researcher, you'll use advanced predictive and prescriptive methods (causal inference, stochastic simulation, Bayesian hierarchical modelling, machine learning and more) to tackle real strategic and operational questions, e.g., forecasting the financial and population health impact of a new service before it launches, building risk models to identify who could benefit from proactive care, simulating the impact of a business case before money is committed, and evaluating whether the care models we've introduced are actually working.

You'll productionise these into tools used across the WNL health and care system, impacting real-world strategic, operational and clinical decision-making. You'll play a key role in ensuring these new data and technologies are used responsibly and ethically to ensure this innovation does not perpetuate existing health inequalities and must feel confident promoting these principles., Independently delivering end-to-end data science projects yielding actionable insights and tools in production that enable users to tackle real-world strategic and operational problems.

Considering user needs, data quality and management, user experience and engagement, deployment, and making best use of statistical and machine learning methods. Rigorously applying appropriate advanced statistical and data science methodologies to generate robust and reliable insights communicated with appropriate levels of uncertainty Maintaining knowledge of a broad range of advanced statistical methodologies to identify and apply the most appropriate technical solution to a given problem, alongside a modelling specialism in line with the seniority of the role Advanced use of open-source analytical tools (including R or Python) to develop and deploy (Snowflake, Docker, Github Actions) models and applications, and to assess and monitor model outputs Set technical standards, actively contribute to high-level architectural decisions and identify development opportunities for yourself and those around you and adopt innovative practices learned from the wider analytics community Matrix management and coaching of senior data scientists to deliver advanced models and productionise tool., Followa data ethics framework ensuring compliance with AI fairness and transparency standardsandmaintainafirmunderstanding of the governance landscape in healthcare Apply understanding of NHS pathways, service interfaces, and operational pressures to ensure analysis reflects real-world context and supports evidence-based interventions.

Working with stakeholders to understand the underlying business need and applying your knowledge and influencing skills to co-designappropriate projectplans including problem articulation, project scoping and design, communication,deploymentand evaluation. Asa proactive member of data science communities,youllcollaboratewithlocalacademic andnationwideNHS partners.Locally you willset technical standards and architectural direction within data science as our stack matures,andsupport other data scientists to develop and deploy advancedsolutions.

If you'd enjoy the freedom to shape a growing data science capability, buildmodelsonarich linked datasetin a cloud native platform, and see your models genuinely change how care is planned and delivered, we'd love to hear from you. Educated to Master level / equivalent experience in Data/analytics field Evidence of post qualifying and continuing professional development Demonstrable knowledge in relevant analytical fields, their associated methods, and their potential for application within healthcare, including advanced statistics, epidemiology, data science, econometrics, and operational research Expert knowledge of the role of analysis in improving decision quality and be capable of supporting advanced decision-making methods (e.g.

multicriteria decision analysis) Expert understanding of advanced analytical methods, including a specialism of one o