Description Statistical analyst SALARY: £37,841 Per Annum HOURS: Full Time or Part Time (Minimum 0.8 FTE) CONTRACT TYPE: Fixed Term (ending 31 December 2030) LOCATION: Research England, Westward House, Stoke Gifford, Bristol GRADE: UKRI D POSITIONS AVAILABLE: 1 CLOSING DATE: 5th January 2026 PROPOSED INTERVIEW DATE: w/b 2 nd February 2026 PURPOSE The Research Directorate is responsible for Research England’s policy development, evaluation and implementation aimed at maximising the excellence and impact of research in universities in England. As a Statistical Analyst at Research England working across the Research and Analysis Directorates, you will be in a key position to design and deliver analytical tools and processes that directly support the allocation of £2 billion of strategic institutional research funding (SIRF) to higher education providers in England. The research funding team is responsible for Research England’s research funding policy evaluation, development, and implementation. Working primarily with key Analysts and the Research Data & Evidence team you will support the development of work areas, from designing and refining funding algorithms and quality assurance processes to delivering new funding mechanisms, while demonstrating a commitment to innovation and continuous improvement. A sound understanding of an analytical product development cycle is crucial for this role, including analysing data using a variety of quantitative methods, evaluating methodologies, and presenting findings. Equally important is experience of quality assurance processes, and an awareness of how these minimise errors in analytical outputs. You will be well-organised and self-motivated, ideally with a background in statistical modelling. Able to work with initiative, you will support the delivery of projects and contribute to their development, while communicating clearly and professionally with colleagues. MAIN OUTPUTS AND ACTIVITIES To support the algorithm-driven allocation of research funds to higher education providers by: developing a sound knowledge of the Higher Education sector data used by the analyst team to underpin SIRF funding allocations. developing a sound knowledge of the algorithm-driven (also referred to as formula-based) research funding methods used by Research England and collaborating with colleagues to develop, maintain and implement funding models. supporting the team by challenging assumptions, considering data and methodological limitations, and suggesting solutions. critically evaluating and justifying the choice of methods and tools, using evidence to select and apply appropriate quantitative techniques for developing formula-driven funding allocation models, suggesting adaptations to approaches to effectively incorporate a variety of data sources. engaging with quality assurance and publication processes for disseminating outcomes. supporting the presentation of high-quality statistical advice and analysis undertaken by the team. To provide broader sector analysis by: supporting the development of new approaches and analytical models that underpin sector benchmarking activities. investigating available datasets and determining possible metrics for use in sector analysis. collaborating with colleagues on possible ways to gain sector insight from datasets and how these could feed data visualisations that may aid in supplying this insight to internal and external stakeholders. To assist with quality assurance checks when required: ensuring that the team QA process is always followed. making sure that QA approvals are escalated as necessary. Other: supporting wider areas of the Research Funding team activities as they arise. ASSESSMENT CRITERIA (S) – ASSESSED AT SHORTLISTING (I) – ASSESSED AT INTERVIEW (S&I) – ASSESSED AT BOTH SHORTLISTING AND INTERVIEW Formal statistical training: Degree in mathematics, or another subject, or equivalent professional experience, containing formal statistical training. (S) Analytical expertise: Knowledge of the practical application of statistical and mathematical methodologies, with ability to develop new approaches for analysing and utilising data, rather than relying on rote application of standard methods. (S&I) Critical evaluation and problem solving: Ability to critically review and assess data, methods, and processes in a careful and systematic way, identify potential issues or limitations, and suggest practical improvements or alternative approaches. (S&l) Programming and data handling: Experience of coding to manipulate datasets. (S&I) Quality assurance and coding standards: Experience of checking the accuracy and reliability of analytical work, including writing well-structured code and following good practices to ensure outputs are correct and easy to maintain. (S&I) Collaboration and project management: Ability to collaborate with colleagues on the development of work areas and contribute to high-profile processes or projects. (S&I) Workload management: Ability to plan and manage a varied workload, adapting to changing priorities effectively. (S&I) Communication and influence: Good written and verbal communication skills, with the ability to clearly explain data and analysis to non-specialists, ask clarifying questions, and engage in constructive discussions with colleagues to explore ideas and develop solutions. (S&I)