By George C.

I remember vividly when the research I started as an intern at Tower finally got a strong simulation result. It felt like one of the great moments in my life – up there with when I found out I was going to the US for college or when I first did 20 consecutive pull-ups. I found myself circling the dorm with a smile I couldn’t wipe off my face.

I began the research during my sophomore and junior summer internships, then picked it up again after joining Tower full-time. By the time it was in production, I had been thinking about the project throughout half of college. In a way, I had grown up with it. That experience captures what I liked most about my two internships at Tower. With my team’s support, from the first day, I was working on a project with the ultimate goal of getting it into production and adding value. I wasn’t working on a project created just to fill a summer; I was contributing to work the team genuinely intended to use. Now that I’m working full-time as a quantitative trader at Tower, I can see more clearly what those internships taught me: how quant firms work, what separates strong research from exceptional research, and what I wanted from the team where I would start my career.

Finding My Way to Quant Trading

I grew up in Romania, where I competed in International Physics Olympiads, and moved to the U.S. to attend Princeton, where I studied Computer Science.  

Quant finance stood out as a career path because it brought together several things that appealed to me. I could continue using the math (i.e., probabilities, calculus, linear algebra, and the art of making useful approximations) and analytical skills I had developed through Physics, but in an environment where research was collaborative and its impact was much easier to see. 

I was particularly drawn to the quick feedback loop. In trading, you can develop an idea, test it in simulation, learn from the results and continue improving it. You don’t have to wait years to find out whether your work is heading in the right direction. 

I also love the objectivity of success in quant research. For example, I like to paint in my free time. Sometimes I spend a week painting what I think is a masterpiece, but then my grandma will find it “so-so.” Other times she’s amazed at something I only spent half an hour on. Quant research is more objective: when my teammate sees hot PnL (profit-and-loss) numbers in his research, I can see the same results and immediately give him credit. 

Taking Ownership of Real Work

When I joined my team as an intern, my manager gave me several possible projects and let me choose which one I wanted to pursue. I chose to work on models for index futures trading because I saw an interesting opportunity there. 

From the beginning, the objective was clear: if the research worked, we wanted to get it trading live. 

That changed how I approached the internship. I knew the project could eventually become something the team used, which kept me motivated even as the research took time. 

My project had a long research cycle. I continued it during a second internship, it was worked on further while I finished college, and I returned to it after joining Tower full-time. Other projects can move much faster. I’ve seen interns on other teams have their work deployed immediately after the summer ends. 

The longer journey made the experience more fulfilling to me. I had the chance to take ownership of an idea early in my career and eventually see it through.  

Learning How Research Actually Works

Technical skills are the foundation for quantitative trading, but some of the most important things I learned were about how to conduct research effectively. 

One was attention to detail. A promising idea can succeed or fail based on small decisions about how you implement and test it: things like what hyperparameter grid you choose for a machine learning model, or how you normalize your model input features, or how you deal with historical prices that seem wrong. When things don’t work as you expected, you have to look closely at the data and keep asking what might be going wrong. 

I also learned how crucial communication is. When you are starting out, you are still developing intuition and learning your team’s systems and codebase. Communicating regularly with my manager helped me get guidance quickly and avoid going too far down the wrong path. 

Those habits have carried over into my full-time role. I still communicate frequently with my team, and I still use the research methodology I developed as an intern: focus on the right problem first, get the data into a good place before optimizing its downstream consumers, and approach each step in the right order.  

Knowing I Wanted to Come Back

My internships taught me a lot about trading and research, but my biggest takeaway was simpler: this was the team I wanted to join full-time. 

I got along extremely well with the people I worked with, and I was surrounded by traders I felt I could learn a tremendous amount from. Even now, that learning curve still feels steep and I consider that a good thing. 

For anyone starting an internship at Tower, my advice is to learn as much as you can about your project, but also about your team, Tower, and the industry around you. The more context you have, the better positioned you are to understand why your work matters and where you can contribute. 

I came to Tower as a student looking to understand what quantitative trading was really like. I left knowing what kind of work made me curious and hungry, who I wanted to do it with, and the research that I wanted to come back and finish.