Chelsea Winskill

Acting Senior Regulatory Data Analyst, Office of the National Rail Safety Regulator

Background: Data analytics

“I never would have thought that I’d find rail interesting but it’s fascinating. There is so much happening in the sector. You’re always learning.

I’m part of the risk and analysis team at ONRSR – the Office of the National Rail Safety Regulator.

I work with some highly intelligent people who have specific domain knowledge, whether that’s tracks or rolling stock, and who enjoy sharing that knowledge.

There’s a lot of collaboration both within our team and across teams. This makes for a great working environment. Whenever there’s a challenge or issue, you’re never short of people who are keen to help you solve it.

It’s also a very diverse environment in culture, gender, age.

Usually, analytics can be male dominated but our team has a very even pool of talent. This reflects the fact we’re trying to get the very best skills possible.

The team I work in is mostly aged under 40, but older workers across the rail sector are really valued. This ensures knowledge isn’t lost. People respect and value knowledge and experience. It’s what you bring to the table that counts – nothing else matters.

At the moment, most of my work is on report automation. This involves designing and modelling data and reports in a way that people can use and access reports for themselves, on demand.

In terms of analytics, some of the work the rail industry is doing is at a really high level. I feel that with the skills and experience I’ve gained I could go and work anywhere. But I’ve been at ONRSR for five years now and have grown to love working in rail and with a team of analysts. We are like minded and I really feel valued in what I do.

I would encourage anyone who naturally finds maths or statistics interesting, who can identify with being a critical thinker, and who enjoys applying their knowledge in practical ways, to give data analytics a go.

Industries like rail are fantastic environments to practice analytics because they are, by nature, technical environments which rely on accuracy, data and expertise for safety, efficiency and quality outcomes.”

To find out more about how to become a Data Analyst or Data Scientist check out our training pathways.