Recent Reflections: From machine learning to quantitative research, Zilin Yan (’22) looks back at her Princeton MFin experience one year after graduating.

While studying economics, finance, and statistics at Tsinghua University, Zilin Yan (MFin ’22) knew that she wanted to continue pursuing knowledge and experience in these industries. During this time, she interned with a quant capital manager, a capital firm, and a hedge fund in quantitative research or analysis, further solidifying her dream career path. Shortly after graduating with her bachelor’s degree, Yan began the Master in Finance program at Princeton’s Bendheim Center for Finance. 

Now, one year out from graduating with a Master in Finance degree—and a year of working full-time in the financial industry under her belt—Yan revisits her time in the program and highlights the experiences that helped shape her goals and path forward. Currently, Yan is a quant researcher at IMC Trading in Chicago, IL, where she had a summer internship during the MFin program.

Lindsay Bracken, BCF’s Manager of Career Development, Alumni Relations, and Corporate Affiliates, recently reached out to Yan to gain her insight on her first year post-graduation.

If you’re a Princeton BCF alumnus who’s reached a milestone in your career, we’d love to hear from you. Reach out to Bracken (lbracken@princeton.edu) to stay in touch and tell your story.

Bracken: After receiving your bachelor’s degree in economics and finance, what motivated you to pursue a Master in Finance degree? What factors led you to choose Princeton BCF’s program?

Yan: During my undergraduate studies in economics, finance, and statistics at Tsinghua University, I became captivated by the notion of employing a scientific, quantitative methodology to comprehend the intricate financial market. After that, I decided to pursue a career in quantitative finance and started to think about advancing my education and launching my career in the United States, where the financial market is among the world’s largest, and the quantitative finance industry is highly developed.

The Princeton MFin program was always my top preference, due to its world-class academic resources, eminent scholars, and beautiful campus. I appreciated the flexibility to choose courses from diverse departments such as ECON, ORFE, SIPA, COS, ECE, and others, to explore my interests. In addition, the theoretical inclination of the curriculum allowed me to delve deeply into the topics I find intriguing. Moreover, the well-rounded academic training goes beyond classroom lectures, with research opportunities to apply theoretical knowledge to practical issues. My experience at Princeton was something I had always hoped for during my master’s studies.

Bracken: Please share your research experiences and any memorable episodes from your time at Princeton.

Yan: As my master’s thesis and part of my Certificate in Machine Learning, I researched the rough volatility model with Professor Robert Almgren, which was also one of my most 

unforgettable experiences at Princeton. For me, researching this topic presented an opportunity to practice applying the technical skill set I had been building up to that point. I was able to take advantage of the great research facilities at Princeton, including their easily accessible computational resources, which allowed me to efficiently run simulations and optimizations when needed. Additionally, this experience taught me how to research effectively in general, starting with how to raise a good research question, how to guide oneself through a research process, and how to face setbacks along the way before arriving at a conclusion, which has been very helpful to my career as a quantitative researcher.

Bracken: Can you tell us about your current role at IMC Trading? How did your internship position turn into a full-time position?

Yan: I am currently a quant researcher on an index option desk. It has been a very exciting experience so far. My daily work involves using statistical tools to come up with new models and solutions to address real-world challenges we find in trading index options and iterate on them through backtesting. I have been growing quickly during the past several months since I finished my training and was placed on the desk. The growth is not only in technical skills such as how to apply stats/CS/mathematical knowledge we learned at school to practical problems, it’s also in how to communicate, cooperate with people, and how to make things happen. For example, I would talk with traders to understand the new challenges in our trading practice, which helps scope out the question I need to address in my research; I also need to work with developers to make sure the algorithm is implemented efficiently in production. Experiencing the steep learning curve, as well as seeing my actual impact in the trading business, makes me even more passionate about the job. 

Transitioning from an internship to a full-time position turned out to be quite natural for me. Initially, I felt a bit nervous, but I quickly shifted my focus toward the invaluable learning experience itself. I began to think more about how I could make the most of this opportunity to gain practical knowledge about option trading from experienced professionals. 

While working on my internship project on the extension of an option trading strategy to a new scenario, I realized the importance of being brave enough to challenge the status quo and contribute new ideas, even as a junior person. With that in mind, I was able to apply the analytical tools I learned and took the initiative to make my own improvements to the algorithm design. My summer internship experience reinforced my desire to pursue a quantitative research career that excites me and keeps me learning new things along the way. I also appreciated the collaborative working culture at IMC, which made my internship experience even more enjoyable. Therefore, when I received the return offer for a full-time position, I did not hesitate to accept it.

Bracken: What are some of the most important skills you gained from Princeton and how have you been applying them to your current position?

Yan: One thing specifically related to my current job was a lecture I took during my final semester: The Political Economy of Central Banking by Professor Alan S. Blinder. In the lecture, I learned a lot about the goals, mechanisms, and culture of the central banks as well as the challenges facing them. Professor Blinder shared stories and his own experience as the Vice Chairman of the Fed, which got me interested in macro-related topics. Later, it was a pure coincidence that I started my career on index options, which is very macro-driven, especially during the post-Covid period. No doubt that the lecture benefited me a lot.

Bracken: Can you elaborate on your experiences in the Machine Learning program as well as AI? How has your Certificate in Machine Learning impacted your career?

Yan: My research of the rough volatility model with Professor Robert Almgren was a big part of my experience in the Machine Learning program. Everything I learned during this program, and specifically my research project, has been invaluable for my career as a quantitative researcher. Moreover, since the topic is of practical interest to the industry, this experience has become a highlight of my MFin journey, and people are often interested to learn more. I really appreciate the exceptional academic resources Princeton provided me with.

As an AI for two courses over two semesters, I had the opportunity to connect with a diverse group of individuals. During my time as an AI for Asset Pricing I, a core MFin course, I was able to build relationships with peers from the next MFin class. Similarly, while serving as an AI for High-Frequency Trading at ORFE, I got to know students from various departments and backgrounds. It was also a great experience to share my understanding of complex concepts with others and engage in thought-provoking discussions that challenged my own views. In the end, these experiences helped me to solidify my own understanding and deepen my knowledge.

Bracken: Now, one year after graduating from Princeton BCF, when you reflect on your experience, what is one thing that stands out the most? And what advice would you give to this year’s graduating class as they begin their careers?

Yan: It’s difficult for me to pick a single perspective, as there are many aspects that have impacted my academic and career development during my time at Princeton. However, I do want to highlight the importance of the relationships I have built with my classmates and alumni. This started even before I began my formal studies at Princeton when I tried to reach out and received great career advice from Princeton MFin alumni—one of the alumni carefully explained all the subtle differences between various roles in quantitative finance, which helped me make a more informed decision on my internship/ full-time job. And these relationships went far beyond the campus, as I kept in touch with my classmates, traveled together, visited each other’s cities, and I even became a colleague with one of my classmates after graduation. The small class size at Princeton helped to facilitate these close relationships. 

Therefore, my advice for the graduating class is to build connections with classmates and alumni. These relationships become an invaluable asset for both career development and personal life.