TfL GRADUATE JOB DESCRIPTION

Data Science Graduate Scheme

Our iconic red buses are the most popular mode of transport for Londoners and we carry on average 5.1 million passengers every weekday. We collect a wealth of data when customers ‘tap’ on the bus and we use this to improve our services and ensure customers have the best possible journey experience

Entry requirements

Already hold or be on track to achieve minimum of 2:2 in a highly numerate degree or a degree with a significant numerate and/or computational component

Location

London (there might be some hybrid working involved depending on a placement)

Duration

2 years

 salary

£27,000

 Job overview

Every day, millions of ‘taps’ are captured through TfL’s ticketing system and indicate where customers get on a bus or enter a tube station; our iBus system provides real-time location information for our fleet of buses and we also help keep London moving with thousands of traffic signals and cameras. We turn this wealth of data into useful information for our customers, so they can plan their travel, and into tools so we can run our services effectively. We’re looking for talented individuals, with a keen interest in transport and data, to join the Data Science graduate scheme starting in September 2022. Over the course of the scheme, you will have the chance to identify your strengths and build capability as you analyse the rich amount of data TfL holds to develop innovative and impactful data science solutions.

What will I be doing?

As a graduate, your data science development programme will consist of up to 4 placement rotations; the duration of each placement will vary but could be anything between 6-12 months depending on the number of rotations. Our aim is to equip you with the range of skills and experience you need for a successful career. We also understand that everyone’s career is different and every graduate’s journey is unique. Here’s an idea of what yours could look like:

Placement 1 – Data and Analytics

Working with different areas of the business to answer key business questions and enhance customer experience. Examples of work undertaken include: using Oyster and Contactless transaction data and WiFi data to develop complex machine learning models to better understand how customers use the TfL network and exploring new data sources such as real-time data to build models that improve customers’ travel experience
 

Placement 2 – London Underground Planning Directorate

Working face-to-face with our maintenance and operations colleagues to analyse and reduce equipment failures. There will be the opportunity to own a project throughout its development cycle from inception to implementing into production, alongside contributing to existing analysis. Examples of work undertaken include: using natural language processing techniques to review written inspection reports and detect underlying causes for train faults; computer vision with train-mounted video to detect broken track fixings and long-term degradation; regression models to forecast asset condition with statistically quantified confidence

Placement 3 – Safety, Health and Environment

Working with the centralised Safety, Health and Environment team on a wide range of projects designed to improve the safety of our customers and colleagues, health of our colleagues and the green future for London. Examples of these projects include: using existing safety incident data to identify causal trends; forecasting incident numbers using varied methods for different time horizons; predicting where collisions are most likely to occur across London and modelling risk to understand the impact of changing our operations or the risk at the platform train interface. You will work with a wide variety of stakeholders including operational staff to put the incident data into context.

Where appropriate, there will be some flexibility to tailor your personal scheme; this could involve lengthening placements or choosing placements with a less technical focus.

Where can this career take me?

Upon completing the scheme, we would expect you to roll-off directly into one of our data science teams.

You will work on both small and large scale projects with other data scientists and non-technical stakeholders from across the business and will be responsible for delivering end-to-end data science solutions. Further down the line, you could expect to be leading data science work streams as well as managing and developing a small team of data scientists. However, as TfL is a large organisation there will be many opportunities to progress.

What training and support will you get?

Whilst on the scheme, we’ll support your technical development in a variety of ways. For example, providing you with time to undertake in-depth learning about a specific data science technique or attending a hands-on training course to learn a new programming language. We’ll offer you some time off should you wish to undertake further study and as part of this, you’ll be able to tap into TfL’s rich data sources for any projects you wish to pursue. We’ll also support your professional development through a combination of classroom-led training courses, online training courses, mentoring opportunities and structured networking opportunities. You will receive one-to-one support throughout the programme from your scheme sponsor and your Line Manager.