Modelling Advancement Lead

Are you excited by the idea of using data and modelling, solving complex analytical problems, turning them into clear, meaningful insights to help shape the future of transport across the UK? Do you have successful experience in working with complex modelling systems and data integration design? Would you like a role where your work bridges evidence gaps, influences national policy, major investment decisions, and real world outcomes? If so, we’d love to hear from you!

We’re recruiting an experienced analyst to join our Transport Appraisal and Strategic Modelling (TASM) division – a friendly, inclusive, expert team at the heart of the Department for Transport’s (DfT) analytical community. Joining our department comes with many benefits, including:

• Employer pension contribution of 28.97% of your salary.
• 25 days annual leave, increasing by 1 day each year of service (up to a maximum of 30 days annual leave), plus 8 bank holidays and a privilege day for the King’s birthday.
• Flexible working options where we encourage a great work-life balance.

Would you like to find out more about the role, the team and what it’s like to work in our department? If so, we are organising an open session where you can virtually 'meet the team' on 27th March at 12:30pm.

About TASM

TASM plays a critical role in conducting analysis and other research to inform decision making processes across DfT: where to invest, how to shape transport policy, and how to build transport systems that work for people and places across the country. Our work includes:

• Developing and maintaining the Department’s Transport Analysis Guidance (TAG) to support business cases for transport infrastructure investments across the UK.
• Building and running national transport models to support policy development.
• Driving the evolution of practices and evidence in transport modelling.
• Producing the National Road Traffic Projections and developing Appraisal Modelling and Evaluation Strategy.
• Providing analytical assurance for major policy and investment decisions.

We currently have two modelling teams:

• Modelling Insights (MI): This team leads the development of national transport models that estimate travel demand and road traffic. They ensure TASM’s modelling and analyses are operated and managed under efficient frameworks and digital infrastructure. They also modernise our modelling capabilities and work closely with data engineers, social researchers, and policy teams to provide high‑quality insight.
• Cross‑Modal Modelling (CMM): This newer team focuses on modelling the whole transport system by integrating transport modes and understanding how they interact across portfolios. They build connections and collaborate with other analytical disciplines to ensure the decision‑making processes are supported with stronger evidence from a multimodal angle. Their work includes land‑use modelling, freight modelling, activity‑based modelling, and developing multi‑modal guidance for TAG.

Across both teams, we have 11 analysts with a range of skillsets who collaborate closely, share ideas openly, and enjoy learning and developing together. We value diverse perspectives, innovative thinking, and a supportive working environment. Our work plays a key role in delivering DfT’s strategic priorities.

The Role

We are recruiting for one Grade 7 role - Modelling Advancement Lead. This role offers the chance to lead important analytical work, shape how modelling is improved while promoting TASM analysis within and outside of DfT, and support colleagues across policy and analysis to deliver impactful results. You’ll also help strengthen TASM’s modelling approaches more broadly. We can tailor responsibilities to your strengths along with TASM’s priorities if you are successful in your application. This role will help shape the future of DfT’s national modelling capabilities.

In this role, you will:

• Lead transformation to our modelling capabilities with Google Cloud infrastructure.
• Integrate our modelling workstreams and redesign data pipelines.
• Visualise and communicate modelling insights clearly.
• Embed scenario‑based analysis into our modelling approach.
• Explore innovative techniques (e.g. machine learning) to build smarter, faster models that improve our capabilities.
• Deliver research to improve modelling data and accelerate model developments.
• Manage one Senior Transport Modeller.

It would suit someone who is familiar with cloud platforms (ideally Google Cloud Platform), enjoys system integration and modernisation, thinks creatively and works collaboratively.