- Joined
- 6/28/25
- Messages
- 3
- Points
- 3
I’m 21 and just graduated a year early from a top-100 U.S. university with a B.A. in Pure Mathematics and Psychology. Like a lot of people, I started college without a clear direction, but I was always drawn to math, not just because I was good at it, but because I genuinely believe it’s the most powerful tool we have for solving real-world problems. Over time, I became passionate about mathematical research and using math to model and understand complex systems with practical implications.
That interest really took off after I participated in an NSF REU in population dynamics and stochastic systems, where I co-authored a technical report and implemented simulations in Python and MATLAB. I loved the process of formulating a model, coding it, analyzing emergent behaviors, and iterating based on the math. It made me realize how much I enjoy applying math to difficult, often messy problems, especially when there's uncertainty involved. Since then, I’ve become deeply interested in quantitative finance, where those same skills are applied to markets, risk, pricing, and prediction.
Right now, I work full-time as a research analyst in a compliance/data-verification role (not super quant-heavy), but I’m actively looking for stronger, more technical jobs while continuing to grow. To stay on track toward my goals, I just submitted my application for Spring 2026 to the online M.S. in Applied Mathematics at Columbia (CVN). It’s a flexible, rigorous program that I plan to complete part-time while working full-time. My elective focus will be on quant finance-related areas like Monte Carlo methods, stochastic processes, and numerical analysis.
Importantly, I also plan to pursue an independent research project or thesis with a faculty advisor, ideally related to quantitative finance topics like stochastic volatility modeling, derivative pricing, or risk forecasting. I want to keep developing as a researcher, not just as a student, so I can eventually contribute to the field, not just work in it.
My goal is to become a quantitative researcher or analyst, ideally in finance, but I’m open to other technical roles that involve heavy math, modeling, and simulation. If the Applied Math MS isn’t enough to break in directly, I’m prepared to apply later to a top MFE program once I’ve gained more experience and saved up. I’m trying to be both ambitious and realistic.
So here’s where I could use some guidance:
That interest really took off after I participated in an NSF REU in population dynamics and stochastic systems, where I co-authored a technical report and implemented simulations in Python and MATLAB. I loved the process of formulating a model, coding it, analyzing emergent behaviors, and iterating based on the math. It made me realize how much I enjoy applying math to difficult, often messy problems, especially when there's uncertainty involved. Since then, I’ve become deeply interested in quantitative finance, where those same skills are applied to markets, risk, pricing, and prediction.
Right now, I work full-time as a research analyst in a compliance/data-verification role (not super quant-heavy), but I’m actively looking for stronger, more technical jobs while continuing to grow. To stay on track toward my goals, I just submitted my application for Spring 2026 to the online M.S. in Applied Mathematics at Columbia (CVN). It’s a flexible, rigorous program that I plan to complete part-time while working full-time. My elective focus will be on quant finance-related areas like Monte Carlo methods, stochastic processes, and numerical analysis.
Importantly, I also plan to pursue an independent research project or thesis with a faculty advisor, ideally related to quantitative finance topics like stochastic volatility modeling, derivative pricing, or risk forecasting. I want to keep developing as a researcher, not just as a student, so I can eventually contribute to the field, not just work in it.
My goal is to become a quantitative researcher or analyst, ideally in finance, but I’m open to other technical roles that involve heavy math, modeling, and simulation. If the Applied Math MS isn’t enough to break in directly, I’m prepared to apply later to a top MFE program once I’ve gained more experience and saved up. I’m trying to be both ambitious and realistic.
So here’s where I could use some guidance:
- Does the Columbia Applied Math CVN path seem like a strong and credible route for someone with my background aiming for quant?
- What internships/entry-level roles or job titles should I look at now that could serve as solid stepping stones? (Especially roles that involve math, modeling, data, or research.)
- Are there projects, certs, skills, or strategies that could help bridge the gap between applied math and finance, especially coming from a non-target background?
- Any advice from people who’ve gone the non-traditional → quant path?