Senior Data Scientist

Job summary

Data science is a broad and fast-moving field spanning maths, statistics, software engineering and communications. Data scientists will often work as part of a multidisciplinary team, using data and analytics to inform and achieve organisational goals.

In this role, you will:

• be inquisitive
• explore and visualise data
• make recommendations to address complex problems and to inform strategic and operational decision making
• use data ethically and appropriately
• be innovative and adaptable
• explore existing and new data using a range of statistical tools and techniques, such as machine learning and predictive analytics
• find patterns in data and transform them into organisational insight

At UKHSA we recruit to a standardised job descriptions for data scientists. We are currently hiring to the following roles:

In the Data Science and Gen-AI team applying advanced data science, and generative AI capabilities to support UKHSA’s strategic priorities to Understand, Prevent and Respond to health threats.

In the Analytical Innovation team designing, developing, and deploying advanced methods and tooling to support public health decision-making. The unit takes a whole systems approach, working with partners across the Agency and externally to improve operational efficiency.

Working for your organisation

We pride ourselves as being an employer of choice, where Everyone Matters promoting equality of opportunity to actively encourage applications from everyone, including groups currently underrepresented in our workforce.

UKHSA ethos is to be an inclusive organisation for all our staff and stakeholders. To create, nurture and sustain an inclusive culture, where differences drive innovative solutions to meet the needs of our workforce and wider communities. We do this through celebrating and protecting differences by removing barriers and promoting equity and equality of opportunity for all.

Please visit our careers site for more information https://gov.uk/ukhsa/careers

Job description

A senior data scientist will work independently and have a good understanding of a range of topics, including data science techniques, delivery methods and stages (such as minimal viable products), tools and technologies.

At this role level, you will:

• develop complex solutions using a range of data science techniques, whilst understanding any ethical considerations
• understand the role and benefits of data science within the organisation
• support capability building within the organisation
• collaborate with others to develop data science solutions and outputs supporting the organisation
• prepare and manipulate data, and perform complex analytics
• present and communicate effectively

In these teams, you will:

Data Science and Gen-AI team

• Build AI and digital solutions that improve surveillance, evidence synthesis and public health response.
• Work with scientific, clinical and analytical teams to deliver secure, scalable products.
• Develop technologies including LLMs, computer vision and analytics platforms for key health programmes.

Analytical Innovation team

• Develop and evaluate novel analytical approaches to improve pathogen surveillance and strengthen biosecurity
• Apply advanced data science techniques including machine learning (ML), generative artificial intelligence, reproducible analytical pipelines, and statistical modelling
• Promote best practice and innovation in data and analytics, building knowledge-sharing networks and strengthening analytical capability across organisation

Person specification

Essential criteria

• Strong proficiency applying analytical and statistical techniques across real-world codebases; practitioner level in SQL and in Python and/or R with fluency in Git-based workflows (branching, code review) testing and reproducible environments.
• Experience in wrangling, cleaning and preprocessing data in readiness for analysis, including working efficiently with large/complex datasets.
• Applied understanding of machine learning approaches (regression, classification, clustering), selecting suitable validation strategies (train/validation/test, cross-validation) and evaluating performance using appropriate metrics (e.g. precision, recall, F1, ROC-AUC) while addressing issues such as imbalance and leakage.
• Working independently and in collaboration with others to deliver multiple concurrent projects, managing scope, risks and dependencies and contributing to team practices (e.g. agile, code reviews, documentation).
• Highly proficient organisational skills with the ability to prioritise, schedule and re-plan to meet tight deadlines. Produces clear technical and non-technical documentation and keep accurate project records.
• Ability to construct and effectively communicate persuasive data stories using fit-for-purpose visualisation with clear narrative, communicating uncertainty, assumptions, caveats and limitations of the data.
• Solid understanding of quality assurance, data validity, reliability and confidentiality issues and statutory information governance requirements.
• Well-developed problem-solving skills and a flexible approach to developing solutions including stages between user requirements to product delivery.
• Excellent interpersonal skills with the ability to influence, communicate, present and capture requirements from technical and non-technical stakeholders.
• Make sound, evidence-based decisions within remit; escalates appropriately with well-reasoned options and recommendations.
• A first- or second-class honours degree in a numerate discipline, computer science or IT equivalent which demonstrates core statistical skills.
• OR have worked in a statistical/data science field and are able to demonstrate continuous professional development in statistics/data science at the same level as a foundation degree/HND (Level 5)

Desirable criteria:

• Understanding of public health and healthcare intelligence, including surveillance, needs assessment, audit, and commissioning support.
• Experience using clinical, epidemiological, environmental, and socio-economic data for public health incident response and research, including data acquisition, linkage, querying, and automated pipelines.
• Strong understanding of epidemiology, including transmission dynamics, surveillance methods, sampling design, bias, and confounding.
• Experience or interest in bioinformatics, pathogen genomics, and molecular epidemiology.
• Experience producing analytical products such as software tools, automated reports, dashboards, and visualisations to support decision-making.
• Experience applying generative AI techniques, including LLMs and RAG

Benefits

Alongside your salary of £41,983, UK Health Security Agency contributes £12,162 towards you being a member of the Civil Service Defined Benefit Pension scheme. Find out what benefits a Civil Service Pension provides (opens in a new window).

• Learning and development tailored to your role
• An environment with flexible working options
• A culture encouraging inclusion and diversity
• A Civil Service pension with an employer cont