Location
Hybrid working based at any of UKHSA's Core HQs: Birmingham, Leeds, Liverpool, and London. Travel to Canary Wharf may be required. Hybrid workers are expected to spend a minimum of 60% of contracted hours (approximately 3 days a week pro rata) at a core HQ.

Hours
Full time, flexible working patterns available including part-time, job-share, and condensed hours.

Salary
Grade 7: £56,185 - £66,581 (National), £58,340 - £68,574 (Outer London), £60,494 - £70,566 (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 Principal Data Scientist, you will lead data science initiatives within the Health Protection Intelligence Systems and Data team, supporting health protection teams and research units. Your role involves exploring and visualising data, making strategic recommendations, and using advanced statistical tools including machine learning and predictive analytics to transform data into actionable insights.

You will maintain and develop data product tools using SQL, R, Python or other languages, develop scalable approaches to manage and analyse genomic data, and manage databases and data pipelines. You will work collaboratively across Genomics and other teams to define project scopes and technical tasks.

This role requires leadership of data science teams, ensuring high technical standards, mentoring, and promoting best practices in coding, data ethics, and delivery of solutions at scale. You will communicate complex data stories tailored to diverse audiences including senior leadership and external forums.

UKHSA values inclusivity and equality, fostering a culture where differences drive innovative solutions to meet workforce and community needs. The role offers continuous professional development and opportunities to contribute to impactful public health initiatives.

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 workflows including branching, code review, testing, and reproducible environments.
- Experience in wrangling, cleaning, and pre-processing large and complex datasets.
- Designing and deploying machine learning solutions with appropriate validation and critique of model limitations.
- Leading and managing data science teams, ensuring effective delivery of programmes and professional development.
- Constructing and delivering compelling data visualisations and narratives tailored to technical and non-technical stakeholders.
- Mentoring in software best practices including modular coding, version control, and peer review.
- Ensuring confidentiality and compliance with statutory information governance.
- Excellent problem-solving skills and user-centred approach.
- Strong interpersonal skills with ability to influence and negotiate within organisational priorities.
- Exercising independent judgement with clear communication of risks and alignment with organisational goals.
- Commitment to equality, diversity, and inclusion, fostering an inclusive and psychologically safe team culture.

About You
You are an inquisitive and innovative data science leader with broad knowledge of data science techniques and tools. You thrive in multidisciplinary teams, are adaptable, and use data ethically and appropriately. You communicate effectively, challenge delivery plans constructively, and advocate for the value of data science. You are committed to continuous professional development and fostering an inclusive culture.

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

Desirable
- Experience utilising diverse data sources including clinical, epidemiological, environmental, and socio-economic data.
- Experience with bioinformatics software and packages.
- Experience in database management and data warehousing.
- Experience producing analytical products such as software packages, automated reports, and dynamic dashboards.
- Experience implementing testing and code refactoring to optimize computational resources.
- Experience deploying machine learning models as part of service development.