Brief description of the host organisation:
The Office for Statistics Regulation (OSR) is the independent regulatory arm of the UK Statistics Authority, which is a non-ministerial government department.
OSR provides independent regulation of all official statistics produced in the UK. As regulators, it is our role to support public confidence in statistics and their use by government, by addressing harms and making sure that statistics serve the public good.
Our statistics regulators work in topic domains evaluating the trustworthiness, quality and value of official statistics and upholding the Code of Practice for Statistics. We also have three key functions to explore cross-cutting issues: Automation and Statistical Methods, Policy and Standards, and Research.
Placement opportunity available
Background: The work of the Office for Statistics Regulation is grounded in the principle that official statistics should serve the public good and inspire public confidence. The potential for new data sources, such as smart data from mobile devices and wearable technology, and new analytical methods, including generative AI, to drive the evolution of official statistics is huge. These developments offer significant opportunities to enhance official statistics but also raise critical questions about how to ensure their trustworthiness, quality, and value. To regulate confidently in this changing environment, OSR needs accessible, evidence-based resources that explain these evolving approaches and their implications.
Outline: This project will explore the current and future role new data sources and new methods play in official statistics production and dissemination. The work will involve engaging with regulators and key stakeholders, reviewing UK and international developments, and horizon scanning for future trends.
Methods: We anticipate this project will involve engaging with OSR regulators to understand the current UK context and consulting key stakeholders, such as Smart Data Research UK, the PADAI network, and statistics producers, to gather wider perspectives. It will include conducting desk-based research to review developments in the use of new data sources and methods in official statistics, both in the UK and internationally, alongside horizon scanning to identify emerging trends and future opportunities.
OSR expects the placement student to take ownership of the project to determine the most appropriate approaches. The student will decide which areas to prioritise and how to structure the synthesis of findings into practical resources, such as fact sheets and SWOT analyses. OSR will provide guidance where needed and help facilitate introductions to relevant individuals and organisations.
Expected output: The project will deliver a set of clear, practical resources for OSR regulators, summarising how new data sources and methods are influencing official statistics. These resources are likely to include fact sheets explaining each data source or method, accompanied by SWOT analyses (Strengths, Weaknesses, Opportunities, Threats) to support evidence-based regulation. The student will require qualitative analysis skills to deliver the project outcomes, although the exact skills required will depend on the research methodology used.
Support: The student will be supported by team members in OSR, and regular catch ups will be arranged with a dedicated project sponsor. The student would also be welcome to attend some wider team meetings, such as the all-OSR team meeting each Wednesday and team training opportunities.
Previous placement students have told us how much they enjoyed working in OSR because we’re a supportive team. We are dedicated to our work but feel strongly about the importance of well-being and work-life harmony.
Skills and experience required for the role
- We are a close-knit team who enjoy collaborating but also work well on solo projects, so the ideal student would enjoy collaboration but also be motivated to work independently.
- Experience in carrying out desk-based research, conducting interviews, and presenting findings clearly would be highly beneficial. Strong analytical and synthesis skills will also be key for creating the expected outputs.
- A student with a background in psychology, sociology, statistics or any social science may find this project interesting, as will those with expertise in data science, artificial intelligence, or related fields given the focus on emerging data sources and methods.
Working arrangements and location of the placement:
- We anticipate the project will last three months full-time, or up to six months if the successful candidate would prefer to work part-time.
- This placement will be completed remotely. OSR may on occasion suggest team wide events or meetings that the student may want to attend in person. If the student chooses to attend, OSR will cover travel and subsistence. Our staff are located around the UK, with our largest offices in Newport (Wales), Edinburgh and London.
- The student will not have access to the host organisation’s IT systems. However, the assigned activities can be completed without this access. The student will need to have access to a computer/laptop of their own and be able to access Microsoft Teams to join calls.
- This opportunity is open to ESRC-funded students who must ensure that the stipend and fee costs can be accessed through their Doctoral Training Partnership (DTP), and the studentship must be extended by the duration of the placement.
How to apply
Closing date for applications: 7th March 2026
Anticipated start date: OSR can be flexible regarding the start and completion date for this project. We would be happy for someone to start from March 2026 onwards.
Application format: Please submit a CV and a cover letter (max 500 words), which includes why you are interested in the role and why you are suitable for it, along with a completed ESRC placement and funding permissions form.
We recruit based on your knowledge and skills, and not background, gender or ethnicity – this is called name blind recruitment.
Please remove references to your:
- name/title
- educational institutions
- age
- gender
- email address
- postal address
- phone number
- nationality/immigration status
How to submit an application: please send your application to regulation@statistics.gov.uk, marking your email for Francesca Gaunt.
Recruitment process: The host organisation is responsible for processing the applications received for this opportunity and applications will be processed as follows:
- Applications received will be independently reviewed by two members of OSR. After reviewing all the applications, the reviewers will converse and agree the candidate who sounds best suited to the opportunity, based on how well the material provided in the CV and cover letter aligns with the opportunity on offer.
- The most suitable candidate will be invited for a short, informal chat before they are engaged.
- This will serve as an opportunity for both parties (OSR and the student) to check understanding and hopes for the project are aligned.
Host contact details: Please send any queries about this opportunity to regulation@statistics.gov.uk, marking your email for Francesca Gaunt.