Are you passionate about using data science to improve healthcare? Join NHS England’s data science teams and play a key role in tackling complex challenges, delivering high-quality insights, and building tools that support better decisions across the NHS.
We value modern ways of working, including transparency, reproducibility, agile delivery, and open-source tools. As a Band 7 Data scientist (Data Wrangler), you’ll collaborate with multidisciplinary teams, developing advanced data science methods, building data pipelines, and producing impactful analytical products.
If you want to make a real difference through innovative analytics and progress your career in a supportive, collaborative environment, we’d love to hear from you.
When applying, please demonstrate your ability in these competency areas: Analytics for Impact, Professional Delivery & Innovation, Engineering, and Leadership & Collaboration.
Duties of a Band 7 Data scientist (Data Wrangler) include:
- Development and maintenance of data science products
- Identification and development of data science applications across policy and operational challenges
- Research and horizon scanning for data science in health and care, including active relationships with academia and industry.
- Provide support to NHS England and wider health and care sector to enable good use of data science.
- Champion adoption of modern ways of working to deliver analytical products (such as transparency, reproducibility, adoption of open-source tools, agile project management)
- Communicate analytical insight in an engaging and impactful way
- Working in multi-disciplinary teams across NHSE to inject data science expertise into delivery of data products.
- Invest in professional development of self and wider team in line with the Data Science Competency Framework for Health and Care professionals.
NHS England has a wide range of statutory functions, responsibilities and regulatory powers. These are focused on supporting the wider NHS to deliver high quality care, as well as doing those things that are best done once for the whole NHS.
Our staff bring expertise across clinical, operational, commissioning, technology, data science, cyber security, software engineering, education, and commercial specialisms — enabling us to design and deliver high-quality NHS services.
In March 2025, the Government announced that NHS England and the Department of Health and Social Care will increasingly merge functions, ultimately leading to NHS England being fully integrated into the department.
If you currently work within the NHS and if successful at interview, we will initiate an Inter Authority Transfer (IAT) via the Electronic Staff Record (ESR). This retrieves key data from your current or previous NHS employer to support onboarding, including competency status, Continuous Service Dates (CSD), and annual leave entitlement. You may opt out at any stage of the process.
Colleagues with a contractual office base are expected to spend, on average, at least 40% of their time working in our offices.
Staff recruited from outside the NHS will usually be appointed at the bottom of the pay band.
We cannot offer visa sponsorship for any vacancies.
You can find further details about the role, including key responsibilities and accountabilities, alongside the organisational structure and person specification in the attached Job Description and other supporting documents.
Your application needs to show evidence of your competence in the following areas:
Analytics for impact
- Apply a range of analytical techniques, in consultation with experts if appropriate, and with sensitivity to the limitations of the techniques.
- Use expertise to propose techniques appropriate to business problem and characteristics of dataset.
- Draw on expertise in several analytical techniques, including their theoretical basis and application.
- Identify key messages from analytical work, translating these into terms for use with either technical or non-technical audiences.
- Report on your own analytical work in sufficient detail, meeting customer needs, effectively presenting results in both written and oral form.
Professional delivery & innovation
- Work with customers to understand their needs, create clear plans and setting priorities which meet the needs of both the customer and the business.
- Deliver good customer service which balances quality and cost-effectiveness.
- Identify areas of potential risk in own and others' work, selecting and using appropriate Quality Assurance methods and suggesting appropriate mitigation of risk.
- Actively identify and take opportunities to promote data science to wider community.
- Experiment with innovations, manage and learn from failures and shares lessons learned within the team.
- Apply knowledge of new and evolving technologies, including open-source software, suggesting appropriate methods and techniques to incorporate in project work.
Engineering
- Use data exploration techniques to understand the characteristics of a dataset, evaluate suitability for subsequent analysis and explain this to other analysts.
- Apply data engineering standards and tools to create and maintain data pipelines.
- Document and communicate the details of data structures to others.
- Design, code, verify, test, document, amend and refactor moderately complex programs/scripts.
- Collaborate in reviews of work with others as appropriate.
- Proactively adopt practices that ensure rigorous and reproducible findings in development of analytical data products.
Leadership & collaboration
- Understand how your work and the work of your team supports wider objectives and meets the diverse needs of stakeholders.
- Focus on overall goals and not just specific tasks to meet priorities.
- Show pride and passion for your work and positive, inclusive engagement with your team.
- Contribute to an inclusive working environment where all opinions and challenges are listened to, and all individual needs are taken into account.
- Change ways of working to aid cooperation within and between teams in order to achieve results.
- Offer support and help to colleagues when in need, including consideration of your own and their wellbeing.
Applicants should use their supporting statement to demonstrate their proven ability across these four areas. Your application will be assessed against these four areas.
