Analytics – where there are no bounds!
Read on to find out how I delved into the all-encompassing world of analytics through creativity and the picture we paint at Wise using numbers. Plus if this peaks your interest, then check out our job board- we’re always hiring into our team at Wise!
I’m a third culture child — ethnically South Asian, bred in Kenya and living in England for nine years. Belonging to three cultures has ignited in me an interest in connected heritages through history, art and anecdotes that show us how cultures in our world are far more similar in their ethos than they are different to each other.
After studying Economics at university I started my graduate job in a large digital consultancy. I quickly learnt that I didn’t enjoy having only surface knowledge, creating more wealth for the wealthy and project life-cycles that span the lifetime of a fly. By the end of my first year, I was yearning to be a part of something more meaningful, with opportunities to delve deeper into a pool of knowledge and work with an end-goal other than creating wealth for shareholders. So what does anyone with an idea but no plan do? Quit and ponder!
I left my job and took some time to assess opportunities that aligned with what I personally find meaningful: knowledge, utility and technology. I remember whipping out my phone and scrolling through all the apps (tech) I had downloaded, trying to find what is useful and value-adding to my life. There shone, in all its glory, the luminous Wise app icon! An app that I often used to transfer money across the two countries I call home, and after every use, left me feeling happy about having saved some money (utility). The third year of my degree was spent working on an empirical dissertation that kindled a passion for research and statistics. I felt a thrill in uncovering human behaviour by assessing ideas through numbers. Therefore, I saw analytics (knowledge) as a space I’d enjoy being challenged by.
I had simple data skills and so spent 10 hours a day for two weeks brushing up on SQL and python to give my best to Wise’s analytics take-home exercise. I passed the exercise, as well as the following interviews, to finally land the job in March last year.
At Wise, my personal goal is to help democratise finance. It’s embroiled in an old banking system with a knowledge gap between genders and classes. Being embedded in the Conversion team, my work primarily focuses on analysing new user experiences and the journey from their first visit to registering at Wise and making sure they find the right product for their needs. Recently, we’ve been working on a funnel analysis to assess how the chronological orders of products users onboard create a significant impact on our user-centred KPIs. The findings will feed into our recommendations on which order to cross-sell products to the users to maximise their savings. We’re then looking to run an A/B test to validate our hypothesis.
The above outlines one of many interesting projects conversion analytics is working on. We also co-work on projects with analysts in other teams and Wise’s diversity makes these projects a novelty to work on. We get to collaborate with people from all cultures and walks of life, and the one most valuable personal takeaway is the friendships we build through this.
Analytics has developed into one of the strongest core functions behind decision making at companies today (as it is at Wise). Before going into analytical methodologies, the groundwork requires ideation, hypothesis creation, assessing measures, all of which are informed by our knowledge and bias. When done by a room of predominantly males, we only create half the picture. There is so much we miss when women aren’t included in setting the rhetoric. Together we can bring to the table diverse schools of thought and can help work through each other’s inherent biases, making our ideas, hypotheses and analytics more robust.
2022’s theme for International Women’s Day is #BreaktheBias. For me, this draws a parallel to Caroline Criado Perez’s book ‘Invisible Women’ where the implications of the absence of women and people of colour in STEM rooms leads to the creation of technology whose design is optimised solely for the white male. The same applies to analytics. When decisions are based on analytics done by a homogeneous group, those decisions overpoweringly benefit that very homogenous group. We need more women in analytics so that we can peel the curtain to reveal the full picture, upon which decisions can be made to benefit everyone.
As a woman, I always gravitated towards creative, aesthetic disciplines and never considered science or mathematics seriously (due to the mental conditioning around these being subjects for males). Numbers were always daunting to me until I played with a python code that allowed me to create geometric shapes on loop and form beautiful designs. This opened up my mind to a world of possibilities within coding and I couldn’t get enough of it. Through my exploration, I gravitated towards analytics given my university experience of writing an empirical dissertation. Analytics can be what you want it to be. It can be creative, it can be practical, it can be abstract. You just have to dive in through the channel you love!
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