Tell us a bit about your life after graduation - where do you work and what do you do in your new role?
I graduated in May 2025 and have since joined Goldman Sachs in Hong Kong as an Equities Quant Strategist. In this role, I work closely with traders on products like index swaps, blending quantitative research with data engineering—many of the skills I developed in the data science program, from model building to large-scale data analysis, are directly applicable here. It’s been an exciting first month, and I’m looking forward to deepening my expertise in market dynamics while contributing to data-driven trading strategies.
What do you feel is the most important skill or lesson that you learned during the program?
Beyond technical expertise in machine learning and deep learning, the program taught me a broader, more critical lesson: technology is neutral, but its impact depends on how we design, deploy, and govern it. Whether as developers, researchers, or users, we shape systems—and with that comes responsibility. The most valuable skill I gained is the ability to see the bigger picture: understanding not just how models work, but their real-world implications, risks, and interdependencies. This perspective—combining technical rigor with ethical awareness—is what enables truly resilient solutions.
Did you have a favorite course at Brown and why?
It’s hard to pick just one! I really enjoyed Machine Learning, Deep Learning, MLOps (my elective), my capstone, as well as DATA 1030 because of their practical, applied nature. I ended up being a TA for DATA1050 and CSCI1420, which I enjoyed a lot. Some of my most memorable experiences came from collaborating with peers on assignments and projects—those late-night debugging sessions and "aha!" moments made the journey a really unforgettable one.
What would you tell a prospective student about the DSI, Brown or Providence as a whole to help them make the most of their experience here?
Providence is a quiet and beautiful town where it's always nice to take a walk during sunny days. The program is tight-knit and supportive—small enough that you’ll know everyone in your cohort, but rich in resources and mentorship. The flexible structure lets you tailor your experience, whether diving deep into research, exploring electives, or balancing internships. I've spent my best two years here and hope it would be the same for you.