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Mehdï Bourai
Mehdï
Bourai
ESG Financial Engineer
Amundi

Charting the Course from Quant Finance to Data Science via the CQF

I took my bachelor’s degree in economics from a French university and also obtained a master’s degree in asset management and financial markets. Then I started my career as a portfolio manager and analyst at a boutique in Paris, where I was working with people from different backgrounds; most of them were mathematicians or engineers from top French engineering schools. It was interesting, and as I wanted to go deeper in the understanding of the underlying math, I started to think about new ways to increase my knowledge. The Certificate in Quantitative Finance (CQF) came into my mind at that time.

 

A few months later, I moved to a large French insurance company and was working on portfolio construction, specifically asset allocation and risk budgeting. In my day-to-day job, we were working with derivatives and thinking about how to manage our portfolios with a more global perspective. At this point, I decided to join the CQF program because it provided a perfect opportunity to go back to the basics of mathematics and quant finance. From option pricing to portfolio construction and risk management, I was able to go deeper into the theory and develop a better grasp of what happens behind the models. One of the essential aspects of the CQF was that each time we were studying a model, we looked at the limitations of that model and how they work in practice. So, in that regard, the CQF gave me a new set of tools to work more efficiently with a fresh perspective on portfolio management.

 

The data science portion of the program was also very interesting. I had significant experience working with data but finding ways to make better use of the data we have at our disposal is critically important. So, with that in mind, the CQF helped me move to a different level in my career. I am now at Amundi in ESG investment and using a great deal of alternative data for data modeling, data cleansing, and analytics. The CQF data science modules continue to be very relevant to this work. In addition, for me the learning has not stopped; since I completed the CQF, I go to the alumni portal almost every week to see the new videos and conferences. This offering helps me to keep my skills up to date well beyond the program itself.

 

In terms of studying during the CQF program, it was challenging, and you must be willing to make some sacrifices. During the course, I spent many weekends studying for the modules, working on exams, or completing my final project, which was related to portfolio construction and different algorithms. At the end of my project, I looked at the results and had deeper insights than I had previously – the goal of the project was to have a full picture of what was going on with the model and the portfolio. After that, I was able to provide comments on the projects that we were engaged in at my job because the insights were relevant there too. So, the time you will put into the CQF is time well spent and if you choose your final project carefully, it can apply directly to your current job or to the job you may be seeking in the future.


To find out how you could transform your career with the CQF program, please download a brochure or join the next online information session to hear more and ask questions to the CQF Program Director.

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