Lead Data Scientist

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 products 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.

Job description Job 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 products 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.

Person Specification

Qualifications Essential

• Master's-level qualification in a relevant quantitative discipline, or equivalent advanced specialist experience.
• Continuing professional development in data science, advanced analytics, programming or related methods.

Desirable

• Relevant professional registration or evidence of wider contribution to the data science or analytical profession.

Knowledge & experience Essential

• Significant experience applying advanced data science, statistical or operational research methods to complex health, care, public-sector or comparable problems.
• Significant experience providing senior technical or professional leadership and leading complex multidisciplinary analytical programmes.
• Strong knowledge of NHS data, including primary care and secondary care data, and experience analysing large, complex or linked person-level datasets, including coding, provenance, linkage, quality and limitations.
• Experience designing, validating and implementing advanced analytical models to support strategic or operational decisions.
• Experience assessing model performance, uncertainty, limitations and potential bias, including documentation, review and ongoing monitoring.
• Experience leading, managing, supervising or developing analytical staff, including setting technical standards and supporting professional development.

Desirable

• Experience designing or delivering quantitative evaluations of services, programmes or interventions.
• Experience applying systems modelling or operational research methods.
• Experience deploying analytical models in operational environments or developing shared analytical assets using cloud-based or modern analytical engineering tools.

Skills Essential

• Advanced programming expertise in R and/or Python, with strong SQL skills and experience manipulating large datasets.
• Ability to apply reproducible analytical practices, including structured code, version control, testing, documentation and peer review.
• Ability to apply reproducible analytical practices, including structured code, version control, testing, documentation and peer review.
• Ability to interpret complex findings, assess assumptions and limitations, and draw defensible conclusions from incomplete or imperfect data.

Person Specification Qualifications Essential

• Master's-level qualification in a relevant quantitative discipline, or equivalent advanced specialist experience.
• Continuing professional development in data science, advanced analytics, programming or related methods.

Desirable

• Relevant professional registration or evidence of wider contribution to the data science or analytical profession.

Knowledge & experience Essential

• Significant experience applying advanced data science, statistical or operational research methods to complex health, care, public-sector or comparable problems.
• Significant experience providing senior technical or professional leadership and leading complex multidisciplinary analytical programmes.
• Strong knowledge of NHS data, including primary care and secondary care data, and experience analysing large, complex or linked person-level datasets, including coding, provenance, linkage, quality and limitations.
• Experience designing, validating and implementing advanced analytical models to support strategic or operational decisions.
• Experience assessing model performance, uncertainty, limitations and potential bias, including documentation, review and ongoing monitoring.
• Experience leading, managing, supervising or developing analytical staff, including setting technical standards and supporting professional development.

Desirable

• Experience designing or delivering quantitative evaluations of services, programmes or interventions.
• Experience applying systems modelling or operational research methods.
• Experience deploying analytical models in operational environments or developing shared analytical assets using cloud-based or modern analytical engineering tools.

Skills Essential

• Advanced programming expertise in R and/or Python, with strong SQL skills and experience manipulating large datasets.
• Ability to apply reproducible analytical practices, including structured code, version control, testing, documentation and peer review.
• Ability to apply reproducible analytical practices, including structured code, version control, testing, documentation and peer review.
• Ability to interpret complex findings, assess assumptions and limitations, and draw defensible conclusions from incomplete or imperfect data.

Disclosure and Barring Service Check

This post is subject to the Rehabilitation of Offenders Act (Exceptions Order) 1975 and as such it will be necessary for a submission for Disclosure to be made to the Disclosure and Barring Service (formerly known as CRB) to check for any previous criminal convictions.

Employer details

Employer name

NHS Central East ICB

Address

Gemini House

Ely

CB7 4EA

United Kingdom

Employer's website

https://www.centraleast.icb.nhs.uk/ (Opens in a new tab)

Employer details

Employer name

NHS Central East ICB

Address

Gemini House

Ely

CB7 4EA

United Kingdom

Employer's website

https://www.centraleast.icb.nhs.uk/ (Opens in a new tab)

Employer contact details

For questions about the job, contact:

Deputy Director of Health Economics and Evaluation

Sam Williamson

[email protected]

Details

Date posted

23 October 2026

Pay scheme

Agenda for change

Band

Band 8b

Salary

£66,582 to £77,368 a year per annum

Contract

Permanent

Working pattern

Full-time

Reference number

644-CE114

Job locations

Gemini House

Ely

CB7 4EA

United Kingdom

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.

Main duties

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.