Computer Science or Math/Economics degree to break in as a Quant?

Alright guys I am a community college student who got accepted to Brown University for Computer Science, and also University of Pennsylvania for Computer Science also. For Math/Economics I got accepted to UCLA and for Computer Science/Business Administration I got accepted to USC.

  1. I was wondering for undergrad, what school do you think will be most advantageous for me to break in the industry as a Quant? I've already finished 3 semesters of Physics and also Linear Algebra with Differential Equations. I can also create applications for the apple store, I don't know if that helps.

  2. As a transfer, am I at a disadvantage when it comes to getting a job in the finance world?

  3. If you were me, what route would you go?

Thanks.

 

You don't have to plan it out right now. There will be many doors open to you as a Penn comp sci major. I know people from that program that have gone into start-ups, established tech companies, investment banking, and quantitative finance.

Since you seem to be interested in quantitative finance, I know a couple of people that have gone directly to Two Sigma / Citadel from Penn on the quant side (lots of people go to Two Sigma on the software side, but that's presumably not what you want to do).

 

Completely agree with Ace Rothstein. To answer question #2, no it shouldn't as I was an undergrad transfer back in the day. If you're doing two years opposed to three at whichever school you select you'll just have to hit the ground running immediately to work on securing solid internships.

"That was basically college for me, just ya know, fuckin' tourin' with Widespread Panic over the USA."
 

Regarding the school choice, Like others said, I agree with Penn.

Also, beyond a perfect GPA, there is two things that are important to asses in your resume before you finish grad school and enter the job market: - 1: Your adaptability to a quant environement : Mastering several quant languages (python+C+sql being a good start), working on dev projects (managing Git, sticking to a project workflow, etc...), mastering basic analytical statistics and pricing-models. - 2: Your edge: Point 1 just makes you acceptable. To enter a HF you need to be above average in at least one specific field. That can be AI in its several aspects, that can be market-microstructure, that can be pricing-models (well no that much anymore today, but used to be).

That in mind, I would try to work on part 1 with a tech intership, not necessarily in finance, but at least data oriented in a dev team. And part 2 with taking as much as possible statistics classes and putting lots of effort in your thesis in a well chosen finance topic.

 

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