A peek into… data & analytics

Graeme Fairnie

Tell us about your role
I’m currently a Data Scientist in the Data & Analytics team. I was working as a statistician previously when I saw a documentary on the Tube, I was fascinated and remembered thinking what an interesting place TfL would be to work. The next day I was on the TfL website searching for jobs and 6 months later I was working here.

I’ve done a few different jobs; started as an analyst then an Operational Researcher and now a Data Scientist. I spend most of time working on projects like the Wi-Fi project where we are using Wi-Fi connections to understand how customers use the network, to better understand the status of stations and platforms, and how busy trains are. Oyster and contactless payments give us a great deal of information about entries and exits but not about what happens in between. The hope is that if we better understand the in-between we can offer customers better information about their journeys and the status of the network.

I’m also looking at a bus project where we collect vehicle location data to help us better understand unplanned diversions on a route and again allow us to give better information to passengers. I also spend a lot of time looking at disruptions; when there is a major disruption on the network we aim to proactively refund customers; this involves identifying the times and places involved, finding customers whose journey time suggests they were caught up in it and refunding them.

Why is your role important to TfL?
Although the projects are interesting and will have long term benefits to TfL on a daily basis the most important thing we do is to refund disrupted journeys. Whether it’s Notting Hill Carnival, the free travel month on the Gospel Oak to Barking Line, or refunds for travel on New Years Eve the work our team does to find the people affected and to get refunds to them really helps our customers. By designing an efficient and repeatable process I help ensure that these refunds can be issued as swiftly as possible.

Icon Transport for London roundel

Millions of people a day travel on our network and knowing that I can play a small part in improving people’s lives really inspires me and everyone I work with.

What’s your favourite thing about what you do?
I enjoy working with the range of people who are at TfL. I get to work with transport modellers, transport planners, software developers, website designers, and fellow Data Scientists. It keeps me interested and although I don’t have a transport background I think the skills I have help bridge the gap between analysis and transport. I also appreciate the opportunities we get to try new things; when I joined I was proficient in a single language (SAS) since then I’ve added SQL, Python/PySpark, Gremlin and I’m currently trying to get my head around Scala.

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How Digital works with Data & Analytics
One example of working with data & analytics was when we were imagining new ways we could use information of customer journeys on our network from the information gathered from station Wi-Fi routers. Some ideas we had included showing live crowding information on our station webpages, showing “live” journey times in our Journey Planner tool based on the time it was taking devices to get from one station to another on a particular route, and suggesting alternative less crowded routes based on alternatives customers were already taking.We started collecting this data in July this year, now Graeme’s team is analysing the data we’ve captured and we’ll see what we’ll see what we can deliver with it!