Meet Naiya, Data Scientist at Zopa

We caught up with Naiya, a Data Scientist at Zopa, to find out more about their journey so far.

Tell us a little bit about yourself and your background

"I studied Aerospace Engineering at the University of Leeds, but for a long time I wasn’t completely sure what career I wanted to pursue. I really enjoyed the problem-solving side of my degree and the challenge of understanding complex concepts, but I realised that I didn’t want to follow a traditional route into engineering design or manufacturing.

Instead, I wanted a role that would allow me to use the analytical skills I had developed while also having more of a human element. As I explored different graduate opportunities, data science stood out because it combines technical problem-solving with understanding customer behaviour and using data to predict what people might do next.

A lot of the work feels like solving a puzzle or doing detective work, which keeps it interesting. I was also excited by the opportunity to learn a completely new set of skills and move into a more fast-paced and agile industry."

What is your role, and how long have you been at Zopa?

"I’m a Data Scientist and I’ve been at Zopa for around a year. Essentially, data science is about using data to identify patterns and make predictions that help the business make better decisions.

I had no previous experience in data science before joining, so I’ve learned a huge amount on the job, from working with large datasets to building and monitoring predictive models. The more I learn, the more I realise there is so much I still don’t know!

Compared with some other analytics roles, data science tends to have a stronger focus on prediction and modelling. Rather than analysing what has already happened, we use data to predict what may happen in the future and turn those findings into tools or models that can support decision-making across the business."

What has been the single most important thing you have learned so far in your job?

"Definitely learning to zoom out and look at the bigger picture. The “so what?” thinking is something everyone at Zopa is taught not only to consider, but to keep at the centre of their work.

Because Zopa is a fast-paced environment that is constantly evolving, we are always thinking about the wider mission rather than simply maintaining the day-to-day tasks. That makes it a really exciting place to work, but it also means that whenever I carry out analysis or put together findings, I’m encouraged to think about how they fit into the wider team and business strategy, and what they actually mean."

What would a normal day look like for someone in your role?

"There isn’t really a typical day, which is one of the things I like most about the role. I could be building a new predictive model, monitoring trends in customer data, checking the performance of an existing model or investigating an unexpected result.

There is also a lot of troubleshooting and detective work involved. We work with large and complex datasets, so part of the job is understanding different data sources, identifying where something may have gone wrong and piecing together the full story. We also spend time with stakeholders across the business to understand the problems they are trying to solve and how data science can support them. No two days are exactly the same!"

What was the application and interview process like, and what did you learn from it?

"The application and interview process taught me that finding the right grad role is a two-way process. Of course, part of it is about showing that you have the right skills and potential, but it is also an opportunity for you to work out whether the role, the team and the company culture are the right fit for you. I found it really useful to ask lots of questions throughout the interview process to understand what the day-to-day role would actually involve, what the team was like and whether I could see myself enjoying the work. I learned not to view interviews as something where you simply have to give the “right” answers, but as a conversation where both sides are trying to understand whether the opportunity is a good match, which definitely takes some of the pressure off!"