Location
Hybrid working based at any of UKHSA's Core HQs: Birmingham, Leeds, Liverpool, London (Canary Wharf). Hybrid workers are expected to spend a minimum of 60% of their contractual hours (approximately 3 days a week pro rata) working at one of the core HQs.

Hours
Full Time - standard Civil Service working hours with flexible and hybrid working options available.

Salary
Civil Service Senior Executive Officer Grade:
£41,983 - £48,128 (National)
£44,148 - £50,121 (Outer London)
£46,310 - £52,113 (Inner London)

About the Role
The UK Health Security Agency (UKHSA) protects public health by preventing, preparing for, and responding to infectious diseases and environmental hazards. As a Senior Data Scientist, you will work independently and collaboratively within the Health Protection Information, Systems and Data team to develop complex data science solutions that support epidemiological analysis and operational delivery of health protection activities.

You will explore and visualise data, apply advanced statistical and machine learning techniques, and transform data into actionable organisational insights. You will build reproducible analytical pipelines and applications, deploy and monitor these using OpenShift and Airflow, and engage with stakeholders to ensure solutions meet user needs.

This role requires a strong ethical approach to data use, innovation in data science methods, and the ability to communicate complex data stories effectively. You will act as a technical subject matter expert, promote reproducible analysis, and represent UKHSA at conferences and in ministerial briefings.

Key responsibilities include:
- Developing complex data science solutions using a range of techniques
- Preparing and manipulating data for analysis
- Building and deploying analytical pipelines and applications
- Collaborating with epidemiologists and other stakeholders
- Supporting capability building within the organisation
- Ensuring compliance with data ethics, privacy, and governance standards
- Contributing to continuous professional development and team knowledge sharing

This role offers the opportunity to work at the forefront of public health data science within a multidisciplinary team, contributing to national health security and operational decision-making.

Experience
- Strong proficiency in analytical and statistical techniques applied to real-world codebases.
- Practitioner level skills in SQL and Python and/or R, with fluency in Git-based workflows including branching, code review, testing, and reproducible environments.
- Experience in data wrangling, cleaning, and preprocessing large and complex datasets.
- Applied understanding of machine learning methods (regression, classification, clustering), validation strategies, and performance evaluation metrics.
- Ability to work independently and collaboratively on multiple concurrent projects, managing scope, risks, and dependencies.
- Excellent organisational skills to prioritise and meet tight deadlines.
- Experience producing clear technical and non-technical documentation.
- Ability to construct and communicate persuasive data stories with appropriate visualisations.
- Solid understanding of quality assurance, data validity, reliability, confidentiality, and statutory information governance.
- Well-developed problem-solving skills and flexibility in developing solutions.
- Excellent interpersonal skills to influence and communicate with technical and non-technical stakeholders.
- Sound evidence-based decision-making skills with appropriate escalation.

About You
- Inquisitive and innovative mindset with a strong ethical approach to data science.
- Collaborative team player who supports capability building and knowledge sharing.
- Committed to continuous professional development and maintaining up-to-date skills.
- Able to engage effectively with a wide range of stakeholders across the organisation.
- Flexible and adaptable to changing priorities and organisational needs.
- Strong communicator capable of presenting complex information clearly.

Qualifications
- A first- or second-class honours degree in a numerate discipline, computer science, IT, or equivalent demonstrating core statistical skills.
OR
- Relevant experience in a statistical/data science field with continuous professional development at a foundation degree/HND (Level 5) equivalent.

Desirable
- Understanding of public health and healthcare intelligence techniques and applications.
- Experience using diverse data sources including clinical, epidemiological, environmental, and socio-economic data.
- Experience producing analytical products such as software packages, reports, and dynamic visualisations or dashboards.
- Experience automating report production and deploying dashboards or APIs.
- Knowledge of code testing, refactoring, and optimisation.
- Familiarity with Kubernetes or similar container orchestration platforms.
- Experience with both R and Python.
- Familiarity with AI concepts and tools.