Raghav Sinha
Computer Science Minor
Trinity College
As a DCS ambassador, Raghav Sinha spent much of his time supporting students across different stages of their computer science journeys. Alongside his studies in economics, statistics and computer science, he developed a strong focus on community and real-world applications of technology.
Now, he is ready to bring those skills into the financial sector, applying data-driven approaches to complex challenges.
This Q&A has been edited for clarity and length.
As a DCS Ambassador and Lead Ambassador, you’ve supported a large community of students. What did you learn from mentoring others at different stages of their CS journey?
Mentoring students taught me that everyone's tech journey looks completely different, and there’s no single "correct" path to success. Whether someone is writing their first line of code or preparing for complex technical interviews, what they usually need is reassurance and a reminder that imposter syndrome is common. I learned that being a good mentor is less about having all the answers and more about being a patient listener and a reliable sounding board.
You also helped build programs like the Alumni-Student Mentorship initiative — what gap were you trying to address for students?
The Alumni-Student Mentorship Program has been a staple for decades, thanks to the incredible work of Kimberly Huynh-Nguyen. With this latest iteration, our goal was to modernize the way we bridge the gap between academia and industry.
Working closely with the team, I focused on bringing fresh, modern workplace insights and strategies into the program so students could better navigate today's rapidly evolving tech landscape. We wanted to give students a realistic, up-to-date view of industry trends, workplace culture and the transition into a modern career.
What first drew you to computer science, and was there a moment during your degree when you knew you’d made the right choice?
Honestly, I was first drawn to CS in middle school because I wanted to automate tasks I was too lazy to do myself — I loved the classic programmer paradox of spending two hours writing code just to save one minute of manual effort. Later at U of T, I knew I made the right choice when I discovered a passion for scalable machine learning. Seeing how code and statistics could intersect to solve complex data problems in corporate and financial contexts completely hooked me.
If you could give one piece of advice to a first-year computer science student, what would it be and why?
Don't spend all your time hidden behind a screen — actively build a community and talk to the people around you. The friendships, study groups and student clubs you join will not only make challenging weeks more manageable but will also open doors to opportunities you might not find on your own. Tech is highly collaborative, so learning to connect with others early on matters just as much as mastering syntax.
What are your interests outside of computer science?
When I'm not diving into tech, you’ll usually find me on the squash or tennis courts or watching the latest Formula 1 race. I also love applied behavioural science and strategy.
What's next for you, and how does computer science fit into that?
This July, I’ll step into the professional world as a full-time data science associate at TD Bank! Computer science fits perfectly into this next chapter, as the programming, analytical and machine learning skills I've built during my degree are exactly what I’ll use to tackle data-driven financial challenges at scale.