I'm a mathematician and studied pure mathematics at the KU Leuven in Belgium. I also have a master’s degree in artificial intelligence and data science from the same university. My master’s thesis was about Von Neumann algebras, which is a part of functional analysis. It also has some aspects of measure theory, which is probably the most useful part for quantitative finance. After graduation, I started working at a financial company, RiskConcile in the regulatory reporting and risk advisory space. For the first time, I began working in options and gained an understanding of what they are and why they are used in trading. When I'd been working there for about three years, I started to consider a range of professional development courses in finance and investment. My boss suggested that I look into the Certificate in Quantitative Finance (CQF). I could see immediately that the content was very interesting, being highly quantitative and also applied.

During the CQF, the focus was not on the type of mathematics that I've worked with before, but instead took me through geometric Brownian motion and stochastic calculus. Previously, I had read some chapters in John Hull’s book, and in terms of interest rate models, for example, I'd heard about the Vasicek model, but I'd never worked directly with these models before. So, I was really intrigued by the range of subjects covered in the CQF program. Even as early as the course Primers we were discussing real world issues in finance. One day, someone explained how the Libor rate was set, another day we looked into things like the cross-currency basis, and other market practices. I didn't know a lot about these areas of finance, but I could see how they would be useful in my work. 
 

On the logistical side, I watched many of the live online lectures and often viewed the recordings again on-demand afterwards because then you can speed up or slow down the lecture as needed. I worked full-time throughout the program, but occasionally I did take a little time off to complete the assignments, especially the final project. I studied very hard for the exams as well and was surprised and delighted to win the CQF Wilmott Award for best achievement in the final exam. Overall, I spent a great deal of time on my CQF coursework, but it was enjoyable, and I learned a lot, so I liked it very much.
 

These days I have been watching more of the lectures for the electives that I had not seen during the program. Naturally, you must focus on a particular track for your final project, but there is much more material available that you can access later on. I’ve also been making use of the CQF Lifelong Learning library; it’s a significant value-added aspect of the program. Looking ahead professionally, up until now, I've focused mainly on Python, but I'd like to get into C++, which has interesting elements that are not present in Python. 

In my current job, we focus, in part, on risk management and we work constantly to develop a broad and deep perspective so that we can better understand and solve the issues our clients are facing. The knowledge that I gained through the CQF program will definitely be useful now and in the years to come. The CQF is quite an intense course, with a wide spectrum of material to learn in a relatively short amount of time. It requires dedication, and I would recommend it highly to anyone who is excited by the opportunity to go deeper into quantitative finance.