Senior Statistical Officer: Road Condition Statistics 49 views

Birmingham, Leeds, London

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Are you a statistician looking for an exciting opportunity to make an impact on how local government plan road maintenance?

Would you embrace the opportunity to work on a high-profile project with significant interest from senior stakeholders?

If so, we have a fantastic opportunity available for a Senior Statistical Officer to join our team and would love to hear from you!

In 2020, the Department for Transport (DfT) published the second Road Investment Strategy, which sets out an investment of £27.4 billion in our strategic road network and the government’s levelling up agenda has increased focus on how investment is spread across the country.

The postholder will be working closely with local transport policy colleagues, engaging with local authorities and industry experts to access new data sources and expand the evidence base of road condition information.

You will be responsible for exploring how to automate outputs to improve the quality of the statistics published by the department. The team are currently working in R and SQL but are open to innovations and improvements as we move to cloud-based environments with a broader landscape of programming languages available. As well as working towards more accessible statistics and transparency, two major cross-government priorities.

In 2019 the transport select committee published a paper of the current standard for monitoring road condition. From the recommendations made DfT have been working with the British Standards Institute (BSI) and Transport Research Laboratory (TRL) to create a new standard. This standard looks to move away from a single technology and open up the market to more innovation.

The postholder will be required to bring this project to a close, but then lead work on the implementation of this standard. With a new landscape of multiple technologies DfT will need to ensure data compatibility and compliance. Alongside exploring the new data and drawing out evidence to fulfil the needs of policy and the industry as a whole.

This project will require engagement across the industry and will have significant impacts on how local government plan road maintenance. This is a great opportunity to work on a key departmental deliverable, work with industry experts and engage with technology developers in this policy-facing project!

Your key responsibilities will include, but are not limited to:

• Managing the completion of the data standard to modernise the method of data collection from local government and work to ensure successful implementation: Supporting policy and analyst colleagues to modernise local road condition monitoring.
• Improving the annual publication: Further developing the automation of the publication, planning how to communicate differences in the data from the new data standard and how to present a dual run of the old and new standards.
• Running local authority consultations: Preparing papers and engaging with local authorities to get changes made to the DLUHC single data list of mandatory deliverables from local authorities to central government.
• Working closely with policy: Road condition statistics are policy facing and you will be required to work closely with policy colleagues.
• Accessing new data sources and expanding the evidence base of road condition information: Leading the work to look at newly emerging sources of road condition data, with an aim to expand the evidence base.

For further information, please see the attached Role Profile.

About you

• You will have experience or an awareness of managing projects and of using coding languages for data manipulation and analysis, with experience of or a willingness to learn R studio or similar.
• You will be a proactive individual who is confident using your initiative to overcome barriers and drive work forwards, but also know when to seek guidance from your line manager before making decisions.
• You will have excellent time management skills and will be highly organised, to ensure delivery of multiple work strands simultaneously, and will remain flexible when faced with ambiguity.
• You will have great interpersonal skills, enabling you to develop positive working relationships with a variety of stakeholders, including with a range of companies throughout the industry, and respond well to feedback received.
• You will be willing to network and take part in industry events.

Additional Information

This role is available to individuals who wish to be spending their office time in London, Leeds or Birmingham, and we would also expect the individual to be willing to occasionally travel to visit different DfT office locations or attend events.

A minimum of 60% of your working time should be spent at your principal workplace, although requirements to attend other locations for official business, or carry out detached duty in another DfT workplace, will also count towards this level of attendance.

To be eligible to apply, you are required to be a member of the Government Statistical Service or hold a professional statistical qualification as per the requirements for membership of the Government Statistical Service:
• A first or second-class honours degree in a numerate subject containing at least 25% taught statistical content (e.g. Statistics, Mathematics, Economics, Sciences, Business Studies, Psychology, Geography, or similar)
A higher degree, e.g. an MSc or PhD, in a subject containing formal statistical training (e.g. Statistics, Mathematics, Economics, Sciences, Business Studies, Data Science, Psychology, Geography or similar)
• Have worked in a statistical or data science field for a minimum of two years and are able to demonstrate Continuous Professional Development in applying statistics or data science at the same level as a foundation degree or Higher National Diploma (level five)
• Have achieved or on track to achieve a level 4 apprenticeship including at least 2 years in a statistical/data analysis field in government and are able to demonstrate continuous professional development in statistics/data analysis.