• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

Which degree to choose?

Joined
11/8/13
Messages
75
Points
18
I know this topic has been asked to death, so I apologize in advance. I've been interested in trading and quantitative finance for a long time and realized that this is the right field for me personality-wise (not cut out to be a trader or investment banker). I was recently accepted to the master's in computer science program at NYU and was told that a computer science degree is helpful in finding work in this field. My undergraduate major was in the social sciences and completely unrelated to finance.

I'm in a lucky position where the math and computer science departments are closely linked and have overlapping courses, so I may be able to internally transfer to the master's program in pure/applied math or financial math (or be looked at more favorably than an outside student if I have done well in the overlapping courses).

For the best chances of being hired as a strategist or structurer on a trading desk (with the possibility of moving to buy side in the future) which degree is better? Here are the approximate rankings for different departments at NYU from US News & World Report and here at Quantnet:

Computer Science #28
Pure Math #10
Applied Math # 1
Financial Math #6

The CS and math degrees are pretty flexible and you can take a lot of electives from both departments. The financial math degree is not flexible. Which degree do you think would open up more opportunities for strats or structuring?

Thanks for any input.
 
Last edited:
Forget the rankings, they're meaningless.

Masters degrees are about jumping through hoops. In order to jump through the highest hoops, and get the highest grades - which is what employers care about - then just choose the courses that you enjoy the most and the ones you have the best background in.

Sad, but true. I made the mistake of picking challenging courses for which I had limited background during my masters because I wanted to learn more about those subjects. Ended up getting a lousy grade which did more harm than good. I should have just chosen the courses I knew I'd get a first in, since that's what employers and potential phd supervisors are looking for from a masters degree.

Any of those courses are frankly irrelevant for quantitative work. People care about your skills - if you can't contribute to an open source project in C++ or python then you're not at the level they're looking for. In fact, the very best way to get hired is to write on your CV "I wrote a significant portion of the bla bla framework in C++ for the open-source browser Firefox. <link to github commits here>" or similar. If you're not at that level, your focus should be getting to it, and you should just collect your degree as a sticker so that when HR look over your CV they don't throw it in the bin straight away.
 
0 chance to get hired as strategist or structurer regardless of the degree u choose

Ok, since structuring is sales-related it's not an option. How about strats? Isn't the role mostly a bridge between the trading desk and IT (doing the programming that IT can't do)? Or do you have to gain experience as a quant developer to qualify?
 
Last edited:
Forget the rankings, they're meaningless.

Masters degrees are about jumping through hoops. In order to jump through the highest hoops, and get the highest grades - which is what employers care about - then just choose the courses that you enjoy the most and the ones you have the best background in.

Sad, but true. I made the mistake of picking challenging courses for which I had limited background during my masters because I wanted to learn more about those subjects. Ended up getting a lousy grade which did more harm than good. I should have just chosen the courses I knew I'd get a first in, since that's what employers and potential phd supervisors are looking for from a masters degree.

Any of those courses are frankly irrelevant for quantitative work. People care about your skills - if you can't contribute to an open source project in C++ or python then you're not at the level they're looking for. In fact, the very best way to get hired is to write on your CV "I wrote a significant portion of the bla bla framework in C++ for the open-source browser Firefox. <link to github commits here>" or similar. If you're not at that level, your focus should be getting to it, and you should just collect your degree as a sticker so that when HR look over your CV they don't throw it in the bin straight away.

Thanks, I had no idea how important GPA was. I had thought a prestigious degree with a 3.4 trumps a less prestigious degree with 3.8. Sorry to see employers are only interested in the GPA and little else.

Does it matter if you are taking only 1 grad course per semester (so maybe 3 classes a year--fall, spring, summer) if you are busy with an internship or do employers care a lot that you're taking on a full schedule of classes?
 
Last edited:
Thanks, I had no idea how important GPA was. I had thought a prestigious degree with a 3.4 trumps a less prestigious degree with 3.8. Sorry to see employers are only interested in the GPA and little else.

What you said is true, but everyone in finance will have gone to a presitgious school, so the playing field is level in that aspect.
 
Back
Top