Senior Data Scientist

The Senior Data Scientist will independently lead substantial analytical projects from problem definition and data specification through modelling, validation, interpretation, implementation and monitoring. They will select proportionate methods, work within established professional standards and ensure that findings are transparent, reproducible and appropriately interpreted.

A. Advanced analytics and modelling

Independently lead complex analytical projects using appropriate statistical, data science and operational research methods.

Select proportionate methods that reflect the decision context, data quality, implementation requirements and limitations of the evidence.

Provide technical advice on analytical methods and interpretation within own areas of expertise.

B. 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 defined data science components of evaluations and contribute to multidisciplinary evaluation of services, programmes and interventions.

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

C. Analytical products, data and quality assurance

Develop, validate and implement analytical products supporting strategic and operational decisions, clearly defining their intended use, population, outcomes, assumptions and limitations.

Apply proportionate validation, sensitivity analysis, peer review and documentation; assess performance and potential bias across population groups.

Work with large, complex and linked health and care datasets, assessing quality, provenance, linkage and fitness for purpose and working with relevant colleagues to secure authorised access.

Use R and/or Python, SQL, version control, structured code, testing and automated reporting to produce transparent and reproducible analysis.

Support monitoring, review and recalibration of operational products, escalating material concerns and contributing reusable code, templates and analytical assets.

D. Insight, communication and implementation

Work with commissioners, clinicians and other decision-makers to define analytical questions and translate findings into clear, actionable recommendations.

Communicate methods, assumptions, uncertainty and limitations clearly to technical and non-technical audiences, particularly where analysis may influence significant service or resource decisions.

Provide constructive technical challenge where methods or interpretations are unsupported, and support stakeholders to implement analytical products and assess their benefit.

E. Professional contribution and project delivery

Undertake peer review and quality assurance in line with standards established by the Lead Data Scientist.

Provide technical supervision, coaching and support to analytical colleagues and contribute to shared methods, standards and resources.

Manage priorities, risks and dependencies within assigned projects and support delivery of the wider data science work programme.

Promote reproducibility, transparency, inclusion, methodological rigour and continuous learning.

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.

Qualifications

Desirable: - Relevant professional registration or evidence of wider contribution to the data science or analytical profession.

Knowledge & experience

Skills