Nat Orme Herbert graduated from The School of Politics & International Relations with a BA in Politics & International Relations with Quantitative Methods in 2019. In this article, she shared an overview of her career journey, how she navigated the support available while at university and some tips and insights for current students.
University Education
I graduated in 2019 with a 2.1 in Politics & International Relations with Quantitative Methods. I focused strongly on the quantitative and political science side of the degree, and supplemented my university work with self-teaching around how statistics and data are used in the professional realm. I focused my dissertation on making a methodological contribution by applying the Random Forest machine learning technique to the study of democracy – which conveniently gave me a good excuse to teach myself Python and some ML methods.
Career related learning and work-experience at University
I regularly took part in the university schemes to gain work experience, including at Easter in my first year where I was placed with a company (now defunct I believe) called MAD Brands where I was essentially given the marketing role for a line of their products for a week.
During the summer break of my first year, I was placed with a company called Sport Lived which ran sporting based gap years in places all across the globe. This started out as a two week placement but I was able to impress the managing director enough to turn it into not only a full summer-break job, but a term-time part-time job too. My role was something akin to a business analyst/researcher: I primarily performed research on new destinations and offerings that the company could expand into, and helped the MD come up with plans to launch a new company.
In my second year, during the Easter break I was placed with a company called MuscleFood. I spent two weeks with them doing strategy and analysis which culminated with me pitching a retention policy to their COO. I came up with a “MuscleFood Prime” idea akin to Amazon Prime which focused on retention through perks and free delivery. I believe they did actually trial this too.
In the summer, the school was able to secure a placement for me with a charity in London called War on Want. They focused on social justice issues and fighting poverty. I was a data analyst for them, performing analysis on their donors and how they could get better retention and increase the donation amounts. I was able to apply a bunch of skills I had learnt through my degree, in particular regression modelling and data visualisation. It was a great opportunity because a charity like that was not used to having any real data capability at all so I was able to provide some really useful insights to them. They even offered me a job for after graduation!
I also was on the committee in multiple years for the Model UN society where I helped run the society in its regular events and also organised its yearly conference for 2019.
The placements in particular gave me the chance to really experience how small and medium organisations run and work. This, I think, is a really invaluable experience. In larger organisations – the kind that you may intern at externally from the uni – you're often given neatly packaged projects that don't really affect anything. In contrast, with these placements, I was a team member and given a wide remit to really get into things. This teaches you skills that will serve you well in your later career: things like handling ambiguity, working with stakeholders, delivering under pressure, and applying theoretical/academic knowledge in a practical setting. I owe a lot of my success in my current career to the skills I developed in those placements.
I also undertook an eight week internship with the Royal Bank of Canada’s capital markets division during the summer break of my second year. This was a solid introduction to how large organisations work, how the culture differs from smaller organisations, and the highly professional end of the spectrum. I think it's worth trying to get some experience like this because, whereas the smaller stuff teaches you very much how to get stuff done, this gave me considerable insight into how you need to work on influencing and managing in order to achieve your goals. The biggest benefit for me personally though was I found out I hated investment banking, hence why I now work in tech!
I would say that I absolutely milked the careers service dry during university. I was hungry to get experience and the careers service was very obliging to help me get it. I was constantly getting CVs and applications checked, I jumped on every opportunity to get a placement, and I attended so so many events. The outcome was that I left university with a good years’ worth of work experience. It put me in a very strong position when applying for jobs (I didn't want to do most grad schemes) which enabled me to push my career in the way I wanted.
Applying For Jobs
I wanted to get into either data analysis or consulting so I mainly applied for grad schemes in consulting and jobs in data analysis. There weren't very many grad schemes in data at the time (and I don't know if there are now!)
I don't recall the exact job boards I was looking at, but I dedicated a lot of time to finding opportunities. There were job boards themselves, plus career fairs, and I also did a lot of looking up potential employers and then searching for their career offerings and grad jobs. I did also reach out to my network that I'd gained through my work experience.
Eventually I ended up getting most offers by applying for regular jobs, rather than ones targeted at uni grads. Those recruitment processes also tend to be a lot less faff: I ended up getting a job in the Civil Service by submitting my CV and having one interview. I was on the same pay as the Fast Streamers, but didn't have to go through the multi-part process they did.
My career route was probably most influenced by my work experience. Getting to see what it was like to apply data analysis in a real setting was what got me most excited. I'm a highly curious person who likes solving problems and the experience showed me that those two things could be massively indulged by a career in data. I always want to know why and figuring out how I can work that out is lots of fun.
Of course, I wouldn't have gone down that route at all had I not been exposed to those techniques and general data analysis concepts through my degree. And I also wouldn't have had the opportunity to explore those options without the careers service providing so many opportunities and so much support.
That support was also massively invaluable when applying for jobs. I got a real knack for writing CVs because I sent each revision over to an advisor. I had lots of catch ups with them too, and even picked up some great advice on doing things like cover letters. I'd get help with specific applications too just to make sure I wasn't missing anything. Without their support, there's no way I'd have gotten the interviews and offers I did.
Early Career
I spent nearly three years after graduation working as a data analyst and statistician for the Department for Education. I initially worked as a recruitment and then HR data analyst for them.
This was basically the wild west of data analysis, where the vast majority of tools, processes, and support that I now take for granted just didn't exist because of the nature of a role embedded within a function like that. But I’d say in many ways that was a blessing in disguise. I had a boss who was really keen to just let me have a go at things and to teach myself a lot of things.
I'd been learning Python before I started with them, so one of the first tasks I did was use Python to automate a bunch of reports. I wanted to learn new techniques, so one of the analyses I did used Monte Carlo simulations; I tried to get a chatbot working to answer questions about HR which taught me about web design, NLP, and servers/APIs (these days I'd use an LLM); I got to present analysis to some really high ranking people in the Department because there was no one else in my area doing a similar thing, so a lot of the usual vertical blocks to exposure didn't exist.
I carried on learning a lot of soft skills too. Stakeholder management was a huge one: with data, a lot of people aren't really going to understand what you're telling them or how to use it, and quite often expect you to either work magic or rig the numbers to give them what they want. Getting a knack for explaining to people why the work matters, why things need to be done in a certain way, and how to keep people happy whilst turning down their demands are really useful skills to have.
I also built a lot of skills in storytelling. This is one of those buzzwords that gets chucked around a lot but basically encompasses your ability to sell people on your work, whether that's through presenting, documenting, or just generally influencing. At various points, there were people I needed to convince. Whether that was my line manager, or a Permanent Secretary, being able to translate raw numbers into something compelling really helped me get stuff done.
I moved onto Trustpilot in 2022 and have been there for three years. It was quite a big culture shock: I went from being part of a 7,000 strong department where everything moved slowly and yet I had limited technical support, to massive amounts of support and a fast paced corporate environment.
It was definitely a learning curve. So many things were more relaxed and so many other things were far stricter. I had to pick up quite a few technical skills, especially around writing good, maintainable code, but also got the opportunity to explore interesting things and then actually deploy them too. Some recent highlights have been using LLMs for topic modelling on review content, and building an anomaly detection system to help us spot complex fraud as it's occurring.
I’m now the technical and strategic lead for a decent chunk of Trustpilot’s data analysis, which means I get to do things like work with execs on data strategy, open up new data products for the company to sell, and be the expert on what all of the obscure numbers actually mean.
Reflections and Advice
Don't sweat the grad schemes. I'm so glad I didn't end up on one because it would have massively restricted the things I was allowed to do in the very early stages of my career. If you're keen on progression, you can skip the queue this way too: I ended up a higher grade in the Civil Service than the Fast Streamers who graduated that scheme.
Do something interesting that suits you over something that pays lots. I spent a lot of time wanting to get into investment banking only to find I hated it. I probably make less money than most of the people I interned with, but I also have fewer heart problems too.
I'd say, most of all, get involved. Learn what you're interested in and what you're not. Work out what it's like to actually do some of the jobs you might want to do. Build skills and get experience before you leave uni so you have an advantage over the people who didn't. Uni is a great time to learn without risk: it's a lot easier to recover from deleting the database if you're an intern than when you're a senior.
Posted on Friday 10th October 2025