Ali Zahin

I'm a fourth-year medical student at Cambridge, on the MB BChir track and graduating in 2028. I spent last year on an intercalated degree in Mathematical Genetics and Bioinformatics, which rekindled how much I actually enjoy maths. The plan is to spend a chunk of this summer, after exams, doing a fair amount of self-study to push it further. If you have favourite books, courses or topics worth recommending, please send them my way. Most of my friends in medicine think the maths year was a strange detour, and most of my friends from the maths year think medicine is. I think the overlap is where the interesting work is.

I build because building is how you actually find out whether an idea is real. Markets taught me that loop early. A model is just an opinion until you put it in front of real money. Medicine taught me that the systems around the most important moments in people's lives are often held together by spreadsheets, fax machines and goodwill, and that nobody else is coming to fix that for us.

The thread is the same across everything I work on. Take messy, high-stakes information and turn it into something a person can actually act on. Sometimes that's a clinical note, sometimes it's a piece of trading research. Long term, I want to be a serial founder, building companies that change how healthcare and technology fit together at the foundations.

My interest in markets started in 2020. During the pandemic shortages I was reselling sneakers, PlayStation 5s, Xbox Series consoles and GPUs into the spike in demand. I rolled the profit from that into NFTs near the start of the cycle and held positions that returned more than 100x at the peak of the hype.

That experience pushed me toward something more systematic and less narrative-driven. I spent a few months building a research stack for crypto futures in Python. The core was a low-latency market-making engine with exchange connectors, an order book reconstructor, and a quote engine pricing off short-horizon microstructure features. On top of that I ran a pipeline of gradient-boosted models (XGBoost) over funding rates, on-chain flows and order-flow-derived signals, with walk-forward validation and a regime-aware portfolio layer.

The basket settled at an out-of-sample Sharpe above 1.2 net of fees. It was a one-off research project rather than something I actively run today, but the discipline behind it (strict data hygiene, honest cost models, the assumption that anything that looks free is probably wrong) is the part I take into everything else I build.

I got lucky. The school I went to, the university I got into, the people I met along the way, none of it was purely merit. I'm aware of that, and I think it comes with a responsibility to actually do something with it. It isn't a guilt trip; it just shapes how I think about what I'm working towards. Medicine, mathematics and technology are the three things I keep coming back to, and I genuinely believe the intersection of all three is where some of the most important problems of the next fifty years will be solved.

I believe in hard work, and I believe in slightly delusional self-belief. Not because confidence is a personality trait worth performing, but because most worthwhile things look impossible before someone decides they aren't. I also think the UK wastes an extraordinary amount of talent. Brilliant people end up on corporate conveyor belts, not because they lack ambition, but because the path is well-lit and the alternative feels uncertain. I get that. I just think it's worth questioning whether comfortable and meaningful are the same thing. Most of the time they aren't.

I really like talking to people. If you're a student trying to figure out how to get into Oxbridge or land your first opportunity, reach out. If you're building something and want a second opinion, reach out. If you think I'm wrong about something, especially reach out. I don't have all the answers, and I'm genuinely more interested in the conversation than in being right.