Brodie Chen

Biography

Education

• M.S. in Computational Finance - Carnegie Mellon University (2024)
• B.S. in Science, Applied Mathematics and Statistics - University of Toronto (2023)

What is your educational/professional background, and how did you become interested in quant finance?

I completed my undergraduate degree in Financial Mathematics and Statistics at the University of Toronto, where I first developed a fascination with the intersection of data, modeling, and markets. That experience inspired me to pursue the MSCF program at Carnegie Mellon University to deepen my quantitative and programming skills. Quant finance became the perfect bridge between my analytical background and my passion for markets—a field where data science and financial intuition truly meet.

Describe your current role and the most fulfilling aspects of your job.

I currently work as a Fixed-Income Analyst in J.P. Morgan’s Securitized Products Group, focusing on Non-Agency RMBS. My role involves building and refining pricing models for residential mortgage-backed securities, analyzing loan-level data, and evaluating structural features like step-up calls, CPR/CDR dynamics, and credit enhancement. What I find most fulfilling is the balance between technical modeling and real-time market impact—seeing how my analysis translates into actionable trading insights and contributes to portfolio valuation and client decisions.

What are the top skills required for success in your role/job?

Very good communication skills and a strong, unique personality.

How did the MSCF program prepare you for your career?

MSCF was foundational in bridging quantitative theory with practical market application. Courses like Fixed Income, Financial Data Science, and Machine Learning gave me the technical depth to analyze securities and build predictive models, while team projects simulated the real-world collaboration I experience daily at J.P. Morgan. The program’s emphasis on coding proficiency and financial intuition directly shaped how I approach pricing, risk analysis, and model implementation in my current role.

What is your favorite memory from your time in the MSCF program?

My favorite memory was organizing and playing in the MSCF Basketball Tournament. It was a fun break from the intense coursework and a great way to connect with classmates outside of the classroom. The teamwork, competitiveness, and school spirit during the tournament perfectly reflected what I loved most about the MSCF community—everyone pushed each other to be their best, both academically and personally, while still having fun together.

What advice would you give to someone considering the MSCF program?

The MSCF program is intense but incredibly rewarding. My advice is to embrace both the technical rigor and the market intuition—learn to code efficiently, think statistically, and stay curious about how markets behave. Leverage the strong alumni network early, build meaningful relationships, and treat every project as a chance to sharpen your practical skills. If you’re passionate about connecting quantitative methods with real financial decisions, MSCF is the perfect place to grow.