Senior Statistical Analyst
Research England
Salary: £46,743 per annum
Contract Type: Fixed Term until 31 December 2030
Hours: Full Time (Part Time min. 0.8 FTE)
Location: Westward House, Lime Kiln Close, Stoke Gifford, Bristol, BS34 8SR
Closing Date: 16th August 2026
Are you looking for a new challenge? An opportunity to work on a major, high-profile, project in a close-knit team and a fast-paced environment? Do you want to use your knowledge and skills in an agile way across a broad range of focus areas, learning new things and innovating along the way? Do you want to work with some of the most highly respected people across the UK’s research community? Then this may be the opportunity for you!
About the Role
As a Senior 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.
Working primarily with key analysts and the Research Data & Evidence team, you will be responsible for managing work areas from the design and development of funding algorithms and quality assurance processes to delivery of new funding mechanisms and be committed to innovation and continuous improvement.
A sound understanding of an analytical product development cycle is crucial for this role, including significant experience of coding, analysing data (including applied quantitative methods), 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 or financial modelling. Capable of working to your own initiative, you will contribute substantially to the development and delivery of projects and be a confident communicator with people at all levels.
Responsibilities
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.
- proactively engaging early and often within and across teams to share analytical results, and to discuss findings, taking data limitations into account.
- using the most appropriate methods and tools to determine and apply appropriate quantitative methods and write code to model formula-driven funding allocations, confidently adapting their approach as required to effectively manipulate a variety of data sources.
- engaging with quality assurance and publication processes for disseminating outcomes.
- taking responsibility for the presentation of high-quality statistical advice and analysis undertaken by self and/or team.
To provide broader sector analysis by:
- supporting the development of 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 partners.
To assist with quality assurance checks when required:
- ensuring that the team QA process is always followed.
- making sure that QA approvals are raised as necessary.
Other:
- developing and leading relationships with internal and external partners where pertinent, potentially including representing RE at meetings and events.
- delegating tasks to colleagues and supporting junior staff as required.
- supporting wider areas of the Research Funding team activities as they arise.
Person Specification
The below criteria will be scored during Shortlisting (S), Interview (I) or both (S/I).
- Degree in mathematics, or another subject - or equivalent professional experience - containing formal statistical training. (S)
- Experience of coding in R language to manipulate large complex datasets. (S/I)
- Strong analytical experience and knowledge of applied quantitative methods, including a track record in the practical application of analysis or research with an in-depth knowledge of the development of computational and statistical methods for solving complex problems and presenting analytical findings. (S/I)
- Proven ability to critically assess data, recognise drivers for change, and identify where data quality issues may have arisen. (S/l)
- Experience of quality assurance processes, and an awareness of how these minimise errors in analytical outputs. (S/I)
- Able to lead developing work areas, with responsibility for high-profile processes or projects. (S/I)
- Strong written and verbal communication skills, to explain sophisticated techniques and results to non-experts, including clarifying policy questions and guiding colleagues in interpretation of data. (S/I)
- Able to plan and manage a varied and demanding workload and respond to changing priorities. (I)
Benefits
We recognise and value our employees as individuals and aim to provide a favourable pay and rewards package. We are committed to supporting employees' development and promote a culture of continuous learning!
We are offering a whole host of family-friendly benefits, including:
- An outstanding defined benefit pension scheme.
- 30 days' annual leave in addition to 10.5 public and privilege days (full time equivalent).
- Employee discounts and offers on retail and leisure activities.
- Employee assistance programme, providing confidential help and advice.
- Flexible working options.
Plus many more benefits and wellbeing initiatives that enable our employees to have a great work-life balance!
For further information on our benefits please see Benefits of working at UKRI.
UKRI is an Equal Opportunity and Disability Confident Employer.
Please note: if you will require sponsorship to work in the UK, as part of your sponsorship application, you (and any dependants travelling with you) will be required to pay costs directly to the UK Home Office for the application before you start your role with us. UKRI is normally able to reimburse some, or all of these fees after you have become an employee, and this can be discussed with the Hiring Manager. For more information, please visit https://www.gov.uk/skilled-worker-visa/how-much-it-costs or contact [email protected].
Work Location: In person
