Data scientist; Data Wrangler

Overview

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.

• 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
• Work 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

• 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.

• Work with customers to understand their needs, create clear plans and set 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 share 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.
• 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.
• 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.

• Post‑graduate degree in a technical subject (such as Statistics, Mathematics,…