Coming from a financial engineering and data science background, I’ve always been fascinated by systematic trading. At the startup, I joined as the main developer, building a quant research app: a platform where traders or researchers can analyze, backtest, and explore strategies in a highly customizable environment without reinventing the wheel. I worked end-to-end, from backend pipelines to frontend analytics features, collaborating with the founding team to turn ideas into working products.
Learning by Doing
One of the best parts of working at a startup was the freedom to move fast and full ownership. I could come up with an idea in the morning, test it in the afternoon, and have it running by the end of the day. With full ownership over what I built, I had the autonomy to make technical decisions and experiment freely. Of course, that freedom cuts both ways, sometimes I had to remind myself to stay focused on the big picture instead of getting lost in interesting but low-impact rabbit holes.
Working end-to-end gave me a front-row seat to how everything connects. From APIs to analytics engines, I gained a deep understanding of every nut and bolt of the system, often picking up new frameworks or libraries on the fly to build what was needed. It was a crash course not just in development, but in how products come together from scratch.
However, it wasn’t all smooth sailing. the focus is always on getting the product out fast. Supporting systems like testing frameworks or DevOps pipelines often take a backseat. This pushed me to create my own debugging workflows and ensure system reliability from the ground up. There were days I questioned whether my approach matched industry standards, or if I was just improvising in the dark. Without many people to bounce ideas off, I had to build my own compass. That process, while challenging, taught me to think independently, make decisions under uncertainty, and stay adaptable.
Finding My Next Chapter
By the time the platform reached its beta stage with core functionality completed and gearing up for production, I found myself at a turning point. The product had grown from lines of code into something tangible that users could screen, backtest, analyze and experiment with strategies just as we envisioned. It felt like finishing a long climb, while revealing a clearer view of what lay ahead.
Throughout the process, I realized that what excited me most wasn’t merely building the platform itself, but the research behind it: conducting feature selection, discovering statistically meaningful signals, modeling market behavior, and testing the robustness of systematic strategies. The deeper I went, the more I found myself drawn toward quantitative research and strategy development rather than engineering alone.
Still, working in a startup taught me things no classroom could: how to operate without a playbook, how to stay calm when things are undefined, and how to make progress with limited guidance. However, with limited resources and few peers to exchange ideas with, rigorous strategy development sometimes meant second-guessing my approach or wondering if I was following best practices.
That said, I’m now ready to grow in a setting that offers structured frameworks, cross-functional collaboration, and mentorship. I’m eager to collaborate with teams, learning from traders, researchers, and analysts to see how diverse perspectives refine strategy development, so I can see how all the components from data pipelines to strategy evaluation operate within a structured, scalable workflow.
From Building to Becoming
Now, I’m stepping into this new chapter with the same curiosity that started it all. This time with more direction, and a clearer sense of how I can refine my skills and make meaningful contributions to research-driven projects.