French engineering student hesitating between a straightforward way towards quant, and a more risky, but potentially more rewarding way.
Hi everyone,
I am a French engineering student at Télécom Paris (Top 3-5 Grande école in France depending on study topic), choosing my final-year master. My long-term goal is quant research, systematic trading, quant trading in a fund.
I have been admitted into 2 masters :
- M2 Data Science at Institut Polytechnique de Paris / École Polytechnique (#1 Grande Ecole in France): ML, optimization, deep learning, RL, data engineering, statistics. Well known master, and the school is extremely prestigious in France.
- M2 Statistics, Finance and Actuarial Science (SFA) at IP Paris / ENSAE (Grande Ecole that is basically in a league of it's own as it is the only finance/stats focused eng school, doesnt have the same prestige as Ecole Polytechnique) : financial time series, econometrics, derivatives, stochastic calculus, risk, portfolio construction, quant finance, plus some ML. Don't mind the name of the master, it's a quant master, it's just that the school has a long history with actuarial studies (you can become an actuary by following a special set of courses from this master).
- From what I hear, this master has excellent quality courses. You can see the professors on the website, many of them have written books about applied maths/quant finance, and many classes are followed together with the well known Master El Karoui or M2MO. The only issue with this master is that it's recent (9 years old), while M2MO or El Karoui are 35 years old. Therefore, it's just less well known. I dont know many alumni, but I know of some working at CFM, QRT, Totsa (Total oil trading), Barclays, Socgen...
My background includes Brownian motion, Poisson processes, martingales, Markov chains/time series, statistical learning, optimization, ML, econometrics, and financial markets.
My GPA is around 3.8/4.0. Relevant grades: 20/20 in Financial Markets, 19/20 in Econometrics, 16.8/20 in Statistical Learning, and 16/20 in Markov Chains/Time Series. Bummer I got a bad grade (11/20) in Martingales (health issues) and probably won't get a good grade in Poisson Process (just fcked up). But probably will get a good grade in the course about Brownian motion.
I have not applied in the US this year. I have applied to ETHz MScQF but got rejected after the interview phase (prof. in interview told me they had 600 applications, 100 made it to interview). A friend of mine applied to CMU MSCF with 3.67/4.0 GPA, while having never studied probability and got in with a 15K $ scholarship (not a joke). We think it's probably due to the current US/foreign situation : ppl just don't want to go there (and who could blame them).
I see two paths:
- SFA → quant internship/job in Europe as part of master → maybe a US MFE/MSCF later. Safer for quant, but perhaps academically redundant with a later CMU/Columbia-type program, not even sure they would let me in because I already have the skills they teach. Perhaps also harder to work outside of Europe and, from what alumni told me, very hard to find an internship. They succeed in finding one, but it takes 200 applications, 50 interviews for 3 offers.
- Data Science → ML/quant internship as part of master → US MFE/MSCF. More complementary for systematic quant research, but riskier if I fail to get into a strong US quant program : I probably won't be able to ever work in quant, or will get a setback. High reward : US quant compensation if it works
I am mainly interested in systematic quant research, alpha research, ML for markets quant roles. I am less interested in actuarial work or regulatory risk. I am a maths guy, and as a maths guy, I like studying maths, but I also don't mind studying ML, as it is maths**.**
My questions:
- Is a US quant degree worth this risk (and the 100k$), even though I can acquire the same, if not better skills, for sure and for 167€ in France ?
- Does the recruiting process of a fund rely more on skills or on the clout of the school ?
- The situation in the US right now is very complicated, but the compensations there are still very high. What are your thoughts for a european like me ?
I really need guidance from people who have been there before me and would be very gratefull !
Thanks!