Applied Computing in Finance personal statement example

Personal statement example

At the end of every Saturday market my aunt tips the cash tin onto a folding table and counts coins into stacks of ten. For two summers I helped her run her bread stall, and the counting was the part I liked most, mainly because the numbers rarely matched. Card payments arrived in one app, cash went in the tin, and a notebook recorded what we had baked. Working out why three sources disagreed by a few pounds became my first real experience of a problem sitting between money and data.

I decided to try to solve it properly. Over several months I wrote a small Python program that read the exported card transactions as a CSV file, took the cash totals and stock counts I typed in, and produced a weekly summary showing sales by product and any gap between expected and recorded takings. The first version was clumsy: it broke whenever the payment app changed its date format, so I learned to parse dates more defensively and to write simple tests before changing anything. Later I added a chart of sales by hour, which showed that sourdough sold out before eleven while rolls lingered until closing. My aunt now bakes fewer rolls and more sourdough. It is a modest tool used by one person, but it is used every week, and building something that had to survive real, messy data taught me more than any exercise with clean inputs.

My A-level subjects have given me a framework for questions like these. In Further Maths, statistics showed me why a single bad Saturday says little on its own, and I began thinking about variance rather than just totals. In Computer Science I enjoyed the work on data structures and algorithmic complexity; for my coursework project I built a revision quiz system with a small database, and I worked with a classmate on the testing stage, swapping programs so each of us tried to break the other's. Being on the receiving end of her bug reports was humbling but useful. Economics added the vocabulary of markets, interest and risk, and reading Burton Malkiel's A Random Walk Down Wall Street made me curious about whether price movements can be predicted at all. I followed this up by downloading historical share prices and calculating moving averages in Python. I did not find a winning strategy, which is roughly what Malkiel would expect, but I learned how easily a pattern in past data can look more meaningful than it is.

Outside school I work Sunday afternoons on the till at a charity shop. It is unglamorous work, but I have come to appreciate how the shop's donated stock, pricing and gift aid records depend on careful, consistent entry by volunteers of very different confidence with computers. I have shown a few older volunteers how to use the stock spreadsheet, slowly, and that patience has made me a clearer explainer. I also play chess at a local club, where I try to resist the urge to calculate everything and instead judge positions, which is a habit I suspect matters in finance too.

I want to study applied computing in finance because the problems I find most absorbing are the ones where code meets money and the data is imperfect. I would like to understand how financial systems are built at scale, how risk is modelled responsibly, and how to write software that people can trust with their accounts. I am aware that I am starting from a market stall rather than a trading floor, but I have learned to build, test and improve something independently, to collaborate on a shared task, and to describe my results honestly. I hope to bring those habits to a demanding degree and develop them much further.