I did a bachelor’s degree in business administration in France and then completed a master’s degree in Finance in London. Since then, I've been working in London; my first job was with an asset manager working on an asset allocation team. Then I moved to an investment consultancy, advising on pension schemes in the United Kingdom. After some time there, doing less quantitative work than I had been doing before, I decided that I wanted to get back into the asset management industry, and work as an investment strategist to have the opportunity to get back to quantitative work in an environment that I favored over consulting.
With the CQF, you still learn the theory, but the lecturer is from a cohort of professional people who work in industry, so they focus on real-life applications in quant finance.
It made sense for me to further my education in terms of quantitative analysis, so I considered three options: the first was to quit my job and go to a full-time master’s degree program, but that would mean a loss of income and hence very expensive. The second option would have been to do a part-time master’s degree, which would mean working three to four days a week for two years while attending classes; this was a viable option, but two years is a long time. Finally, there was the Certificate in Quantitative Finance (CQF), which I could do in as little as six months while I was working full-time and it was much more focused on what I wanted to do. With the CQF, you still learn the theory, but the lecturer is from a cohort of professional people who work in industry, so they focus on real-life applications in quant finance.
This was very helpful during my interviews, when I was able to talk about not only the high-level theory of the financial models, but also their detailed implementation in a programming language.
Another aspect of the program that was really important to me was the focus on programming skills. In my previous job I had not done much coding, but I knew it would be necessary in an investment strategy role to develop tools for handling data and doing time series analysis. Once I enrolled in the CQF, I did the programming Primer and then attended all the online Python Labs. I really tried to understand how the programming languages worked and I learned a lot. This was very helpful during my interviews, when I was able to talk about not only the high-level theory of the financial models, but also their detailed implementation in a programming language.
The lectures were really high quality and I worked hard in each module. While I was in the program, I started interviewing for the investment strategist positions I was interested in. After several interviews, I received two offers and now I am at JP Morgan Asset Management. My team is quantitatively minded and I'm very happy now. It's wonderful in terms of staying engaged with the CQF program too. Recently, I went back to the CQF portal and looked at the list of electives for the final projects; I will go through some of them, besides the ones I already completed. I also went into the historical database of lectures and masterclasses and have watched some of them as well. My advice to new CQF students is to absolutely make the most of it. You can spend many years looking at this material and you'll still learn something. In addition, the network is quite important; there are many CQF alumni around and it is great to be part of this active community of quants.