Principal Statistical Methodologist
- Civil Service
- Part Time
- Newport
- 56,861
Job Description
Job summary
The Office for National Statistics (ONS) is the UKs largest producer of official statistics, covering a range of key economic, social and demographic topics. These include measuring changes in the value of the UK economy, estimating the size, geographic distribution, and characteristics of the population, and providing indicators of price inflation, employment, earnings, crime, and migration.
Methodology and Quality Directorate (MQD) ensures that analysis carried out by ONS and the analysis community across government is aligned with the Statistics Authoritys strategic vision and relevant quality standards. We aim to improve the rigour and cost effectiveness of regular statistical outputs and the quality of data used for both statistical purposes and more widely in government. We provide advice and guidance on best practice and ensure that new methodologies deliver improved statistics. We seek to exploit technology and emerging methodologies to research and develop innovative solutions to new and existing issues. We provide a forward-looking, efficient, professional, and accessible service to our stakeholders.
Quality and Improvement Division is a key enabler for improving the quality of statistics and data across government. We aim to apply innovative and diagnostic approaches to promote and embed good practice in quality across government, with a focus on communicating the quality of statistics and data. Our work is governed by the Code of Practice for Statistics. The teams interventions include developing and promoting guidance and case studies, implementing quality strategies, running quality reviews, designing and delivering training courses, seminars and workshops, consultancy and advising and creating supporting collaborative, cross-government networks and the collection and monitoring of the cost (compliance) that falls on businesses and local authorities in responding to GSS surveys. The work is aligned closely with the strategic priorities of the UK Statistics Authoritys Office for Statistics Regulation (OSR) and of the National Data Strategy. The division directly supports emerging priorities from the National Statistician.
Methods and Statistical Design Division helps ensure that ONS statistics are unpinned by robust methodology and meet accepted quality standards. The Division aims to improve the rigour and cost-effectiveness of regular statistical outputs, as well as providing advice and guidance on best practice, ensuring new methodologies deliver improved statistics that align with the strategic direction of the office. We seek to exploit technology and emerging methodologies to research and develop innovative solutions to new and existing issues, and provides a forward-looking, efficient, professional, and accessible service to its stakeholders.
Job description
Principal Statistical Methodologists in MQD are responsible for a variety of technical and branch-head roles across a range of specialist subject areas. As examples, areas of expertise which a Grade 7 might lead include, among others: Time Series, Statistical Disclosure Control, Sample Design or Data Linkage. This role will be based in the Integrated Data & Methods Hub and will have initial responsibility for data linkage and assurance, particularly in relation to Census. Each Grade 7 is responsible for organising and delivering a programme of different projects for a variety of stakeholders, working with them to determine their needs, and supporting them pro-actively and often at short-notice with ad hoc requests; sound project management and organisational skills are required in these roles.
Each Grade 7 is responsible for organising and delivering a programme of different projects for a variety of stakeholders, working with them to determine their needs, and supporting them pro-actively and often at short-notice with ad hoc requests; sound project management and organisational skills are required in these roles.
This role sits within our TLFS Methods team where there is a need for a G7 role to provide strategic oversight and assurance across Sample Design and Estimation methods for TLFS. The successful candidate will play a key role in ensuring a consistent and integrated approach across work areas, supporting the integration of new developments and helping TLFS Method project run smoothly and effectively.
Key Responsibilities:-
- Co-lead the methodological development of TLFS methods, with a particular focus on sample design, estimation, weighting and related methods needed to support high-quality labour market outputs (working closely with another Principal Methodologist and the G7 Project Delivery Manager).
- Provide strategic oversight and methodological assurance across TLFS Methods work areas, ensuring a coherent and integrated approach across sample design, estimation, quality assessment and related methodological developments.
- Lead and coordinate methodological and analytical research projects that support TLFS transition, readiness assessment, quality improvement and delivery of agreed measures of success.
- Work closely with TLFS programme colleagues, Labour Market Division, operational teams and other stakeholders to understand requirements, agree priorities, manage dependencies and ensure methods work is aligned with programme delivery needs.
- Engage with academic experts, external assurance groups and wider methodological specialists to test, challenge and strengthen the proposed methodological approach for TLFS.
- Translate complex methodological issues into clear advice for senior stakeholders, governance forums and non-specialist audiences, including explaining risks, trade-offs, assumptions and implications for outputs.
- Provide technical leadership and quality assurance for methodological outputs, ensuring that work is robust, well documented, reproducible and suitable for use in the production of official statistics.
- Support the integration of new methodological developments into TLFS delivery, including identifying where further research, testing or assurance is needed before methods are adopted.
- Lead, support and develop Methodologists and Assistant Methodologists, providing technical coaching, quality assurance and professional development in statistical methods, coding and analytical practice.
- Contribute to the wider leadership of Methodology and Quality Directorate by sharing learning from TLFS, promoting good methodological practice and supporting cross-cutting statistical improvement activity.
- Safeguard the wellbeing of your team and those you manage, creating an inclusive and supportive environment in which people can deliver high-quality work.
- Work to a G6 Senior Principal Methodologist, providing clear advice, escalation and assurance on methodological risks, delivery issues and stakeholder concerns.
Person specification
Essential Criteria
- Extensive knowledge and practical experience of statistical methods and their application within official statistics, with established expertise in developing, evaluating and delivering sample design, estimation, weighting and related methods. Experience in applying methodological expertise to complex statistical challenges and providing robust methodological assurance for statistical outputs.
- A strong track record of leading methodological and analytical research and development, delivering complex programmes of work to a high standard and driving methodological innovation. Experience of leading and developing analytical teams through coaching, mentoring, training and quality assurance.
- Excellent communication, engagement and influencing skills, with experience of providing statistical advice and consultancy to a wide range of stakeholders, including senior leaders, operational delivery teams, academics and external experts. Able to build effective relationships, communicate complex methodological issues clearly to specialist and non-specialist audiences, and influence decisions through evidence-based recommendations.
- Strong statistical computing and reproducible analytical skills, with substantial experience of programming in R and/or Python and applying these skills to methodological research and production. Demonstrates good practice in code development, including code review, version control using Git, and the application of Reproducible Analytical Pipelines (RAP) principles to produce robust, efficient and transparent analytical solutions.