Lead Data Scientist in Ely

Job overview

The Lead Data Scientist is a senior technical and professional leadership role within the Strategic Value Unit, working across the integrated Strategic Value Unit and Population Health Unit function. The postholder will lead the data science discipline, ensuring that advanced analytical methods support strategic commissioning, population health management and evaluation.

Working with large, linked health and care datasets, the postholder will lead the development of robust models and analytical tools and translate complex findings into practical insight. They will work within a multidisciplinary decision intelligence function, collaborating with analysts, health economists, public health specialists, commissioners and clinicians to ensure analysis informs decisions, supports implementation and improves outcomes.

Proposed Interview dates: 19th - 20th November

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The postholder will lead complex analytical work. They will determine where advanced data science methods add value, select proportionate approaches and provide technical assurance for high-impact analytical products.

The role will:

• provide professional leadership for data science across the Strategic Value Unit and Population Health Unit function;
• lead advanced analytical programmes supporting strategic planning, commissioning, population health management, and evaluation;
• develop and apply forecasting, predictive, risk, segmentation, scenario, simulation and machine-learning methods where these strengthen decision-making;
• lead the development and assurance of analytical tools, including population segmentation, risk stratification and case-finding approaches;
• establish standards for programming, version control, documentation, peer review, model validation and lifecycle management;
• assess model performance, uncertainty, limitations and potential bias, ensuring methods are transparent, reproducible and used responsibly;
• translate complex analysis into clear insights and actionable recommendations for senior leaders, commissioners, clinicians and operational teams;
• work with stakeholders to embed analytical products into strategic and operational decision-making and monitor their continuing effectiveness; and
• build organisational data science capability through line management, coaching, technical supervision and the development of reusable methods and analytical assets.

Working for our organisation

We are committed to promoting equal opportunities to achieve equity of access, experience and outcomes and to recognising and valuing people’s differences. We are passionate about creating an inclusive workplace that promotes and values diversity; we see this as a strength and part of our founding mission, values and behaviours. We know through experience that different ideas, perspectives and backgrounds create a stronger and more creative work environment that delivers patient outcomes.

We are committed to creating the best place to work, where your contribution is valued, your wellbeing is supported and all our colleagues can reach their full potential. We welcome and encourage applications from all areas of the community, who meet the criteria for the role, regardless of their protected characteristic. We work to ensure that our recruitment processes are as inclusive as possible to everyone, including making adjustments for people who have a disability or long-term condition and support with the recruitment process for people with lived experience.

We are happy to discuss flexible working options for all roles.

We operate a Carer friendly working environment that is supportive and inclusive. We actively encourage Carers to self-identify themselves.

We are a Disability Confident Employer and commit to shortlisting suitable applicants who meet the essential criteria for an interview. Please inform us of any adjustments you may require.

Detailed job description and main responsibilities

A. Professional leadership and strategy

· Lead the data science discipline across the integrated Strategic Value Unit and Population Health Unit, providing authoritative professional advice and setting the direction for its development.

· Work with the Head of Evaluation and other professional leads to align the analytical work programme and data science capability with ICB priorities.

· Identify where data science can materially improve decisions and advocate proportionate approaches based on the question, available evidence and intended use.

B. Advanced analytics and modelling

· Lead complex analytical projects using appropriate statistical, data science and operational research methods.

· Apply techniques such as predictive modelling, machine learning, forecasting, segmentation, optimisation, simulation, systems modelling and scenario analysis where they add value.

· Ensure methods reflect the decision context, data quality, implementation requirements and limitations of the evidence.

C. Strategic commissioning, population health, and evaluation analytics

· Lead advanced analysis of population need, inequalities, demand, utilisation, capacity, outcomes and variation to support strategic planning and commissioning.

· Apply analytical methods to option appraisal, population segmentation, targeting, pathway redesign and neighbourhood-level decision-making.

· Lead the data science components of evaluations and contribute multidisciplinary evaluation design and delivery of services, programmes and interventions, assessing impact, effectiveness, equity and implementation.

· Integrate quantitative findings with clinical, public health, economic, operational and qualitative evidence.

D. Analytical products, assurance and governance

· Lead the development, validation and implementation of analytical products supporting strategic and operational decisions, including risk stratification, case-finding and population segmentation tools.

· Define each product’s intended use, population, outcomes, assumptions and limitations, with proportionate arrangements for validation, sensitivity analysis, independent review and documentation.

· Assess performance and potential bias across population groups and ensure operational products are monitored, reviewed, recalibrated and retired where appropriate.

E. Data and analytical engineering

· Provide senior technical oversight of large, complex and linked health and care datasets, including their provenance, coding, completeness, linkage quality, limitations and fitness for purpose.

· Work with data engineering, architecture and information governance colleagues to define requirements and secure reliable, authorised access to analytical data.

· Lead reproducible analytical practice using R and/or Python, SQL, version control, structured code, testing, peer review and automated reporting.

F. Insight, influence and implementation

· Work with decision-makers to define analytical questions and translate findings into clear recommendations for strategy, commissioning and delivery.

· Communicate assumptions, uncertainty and limitations clearly, particularly where analysis may influence significant service or resource decisions.

· Provide constructive challenge where methods, assumptions or interpretations are unsupported or potentially misleading.

· Support stakeholders to implement analytical products and assess whether they continue to deliver their intended benefit.

G. Team and portfolio leadership

· Line manage the Senior Data Scientist, Data Scientist and Clinical Policy Data Analyst, including objectives, appraisal, performance, development and wellbeing.

· Provide technical supervision, coaching and professional development across the analytical function, fostering curiosity, constructive challenge, inclusion and continuous learning.

· Lead a portfolio of complex analytical work, balancing priorities, risks, dependencies, resources and timescales to deliver high-quality outputs.