My Journey into Analytics
Sometimes I ponder what 20 year old me – just about to start university, freshly moved to the UK from Hungary – would think about me today. I bet she would be confused; after all, I went from studying Anthropology to working in Analytics, a field I was certain would be closed to me since I knew I just wasn’t that good in maths.
I had an early aptitude for it but when the subject became more difficult I struggled with performing on the same level. In the end, I – alongside my teachers – accepted that I was just not good at maths – but then they implied that girls rarely are – and I was advised to focus on paths more reliant on Arts & Humanities or Soft Sciences. If not for the compulsory research methodology courses at university I probably would not have realised that you don’t need to be a maths genius to enjoy analytics or be good at it. Nor do you need it to learn how to code. It’s much more important to have a problem-solving mindset, good critical thinking, communication skills, and a strong attention to detail.
So I applied for my first analytics job out of university after which I went on to do a Master’s in Economic Policy. While studying for my Master’s I interned at a retail bank which was great for picking up practical SQL and Python skills but felt a bit lacking when it came to providing a mission I could stand behind. That problem was solved when while scouring LinkedIn for interesting opportunities I came across Wise and after a few interviews I started as a business development analyst working with the sales teams selling Wise’s enterprise product offering. That was over 3 years ago and now I work with the Wise Platform team as a product analyst, helping the team understand customer behaviour and prioritise the most impactful opportunities for our platform partners.
Wise Platform works with a large variety of partners from neobanks to software companies, allowing them to tap into the Wise network and giving them and their customers access to cheaper, faster international payments. The team is truly multicultural with members in all major offices from various different backgrounds that allow us to create the best product offering possible. It also means you have many go-to people for travel advice! 🙂 I get to work on various projects from scoping out new product developments to improving our existing data structure and unlike in previous companies I am not simply a ‘data-fetcher’ but a partner in the whole process. And to think that I almost missed out on this opportunity just because I believed I wasn’t good enough for analytics!
I know my experience is not an isolated one; I’ve had conversations with many women who felt intimidated by career paths usually associated with STEM subjects. Who felt that in order to do well in careers associated with those subjects they needed to be at the top of their class to show that they had potential (#notlikeothergirls). Who felt that it was exhausting to keep pushing back against the stereotype of women being bad at maths and not belonging in those fields and just went with an alternative that was marketed as better suited to them.
Who as a result ended up foregoing a career in a field like analytics or had to battle rounds and rounds of imposter syndrome since their analytics journey came with a few detours.
Unsurprisingly, this is not good for the improvement of the field of analytics. It is well-known that the underrepresentation of women in data science increases the risk of biased interpretation of data and can result in data-driven policies being implemented – or data-driven products being created – that don’t serve them well. So not only are women missing out on great career opportunities, we are all missing out on great solutions and products simply because the people working on the numbers behind them are way too similar.
This year’s theme for International Women’s Day is #BreaktheBias and I’ve tried to do so by urging women I know to question their own internalised biases. I’ve challenged sweeping statements like ‘I can’t do this because I’m just bad at maths’ and empowered friends and colleagues to take on projects where they needed to apply analytical thinking. While I for once did not set up any metrics to measure it, on an anecdotal level the experiment has been successful.
You can do analytics. Even if you were bad at maths in school, even if you only took up coding as a hobby – or if you’re only thinking about it now! As long as you make sure you have your problem-solving and critical thinking hat on, the only thing you need is the right topic and the right environment. And talking about the right environment, would you look at that, we’re hiring at Wise so if any of this resonates with you, don’t hesitate to hit that apply button!
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