Hope someone could give me some suggestions on how to choose between the two programs.
I have physics & data science background and some quant trading internship experience. I originally planned to apply for MFE programs but found myself very attracted to computer science. So I applied to some CS programs which I would be likely to get in. I finally got offers from Berkeley MFE Spring 2021 and CMU MITS (Master of Information Technology Strategy) Fall 2020.
I am willing to go to either program. My main expectation for graduate study is to find a job in the US after graduation. I hope I would become a quant trader or researcher. I know it's extremely hard. And I am open to data scientist (works for both programs) or software engineer (only if I choose CMU). I guess CMU MITS is in general a weird choice for people in this forum. Personally (probably because I have no background in finance/econ/biz), I mostly like technological parts of quant work, like programming, CS, DS, probability, etc. and I have no passion in finance as a subject in a theoretical sense. And I believe the quant industry needs people with hard core technical skills, like stats/coding/analytics/systems. And a CS program might be good for building up some tech skill sets in the long run. But I'm concerned that I might be too naive on this issue.
Here are some pros and cons for both programs:
CMU MITS (Master of Information Technology Strategy)
Pros:
- A program under the School of Computer Science (#1 CS school)
- High priority and large freedom in course selection, can take basically all popular ML/Software/Systems courses at SCS
- Very high quality courses and competitive environment
- Small class size, like 20 per cohort
- Good placement, lots of Amazon AWS, heard 100% since the program started
Cons:
- No internship, must take a summer semester in order to complete 4 semesters in 1.5 years
- Bad location, Pittsburgh, not like NYC or bay area
- Significant internal competition, so many talented programmers, 1000+ CS masters applying for similar jobs every year
- Not a popular program, the program is originally designed for cybersecurity, not a traditional CS/DS program, though it turns out to be flexible
- Generally new and small, no public stats on placements and salaries etc.
- Not so well known as Berkeley in non IT-related fields
- Lack of help in job search, basically just LeetCoding, resume, coding tests, interviews, etc.
Berkeley MFE
Pros:
- A traditional MFE program with stable historical placement data
- Good placement numbers, at least up till now
- Responsible program director and great career services
- High bar in admission, admitted students seem to have very outstanding background
- Good program reputation, and good school title
- Good location, near bay area
- A 12-week internship covered (most likely)
- Target on obtaining a quant job
- Network resources, alumni, fellow students, professors, lecturers etc.
Cons:
- An MFE program in a business school, courses are mostly finance-related, technical courses (required to complete online) are not taught on campus
- Probably unlikely to learn very technical things, like ML/CS/Systems/Software, as in CMU SCS
- Knowledge taught in traditional MFE programs are becoming more and more esoteric and useless
- Most likely to be placed in banks, still needs strong individual Math/CS abilities to land a job in buy-side
I'd really appreciate it if someone could give me some suggestions on career path and the current situation in the quant industry. Thank you!!!
I have physics & data science background and some quant trading internship experience. I originally planned to apply for MFE programs but found myself very attracted to computer science. So I applied to some CS programs which I would be likely to get in. I finally got offers from Berkeley MFE Spring 2021 and CMU MITS (Master of Information Technology Strategy) Fall 2020.
I am willing to go to either program. My main expectation for graduate study is to find a job in the US after graduation. I hope I would become a quant trader or researcher. I know it's extremely hard. And I am open to data scientist (works for both programs) or software engineer (only if I choose CMU). I guess CMU MITS is in general a weird choice for people in this forum. Personally (probably because I have no background in finance/econ/biz), I mostly like technological parts of quant work, like programming, CS, DS, probability, etc. and I have no passion in finance as a subject in a theoretical sense. And I believe the quant industry needs people with hard core technical skills, like stats/coding/analytics/systems. And a CS program might be good for building up some tech skill sets in the long run. But I'm concerned that I might be too naive on this issue.
Here are some pros and cons for both programs:
CMU MITS (Master of Information Technology Strategy)
Pros:
- A program under the School of Computer Science (#1 CS school)
- High priority and large freedom in course selection, can take basically all popular ML/Software/Systems courses at SCS
- Very high quality courses and competitive environment
- Small class size, like 20 per cohort
- Good placement, lots of Amazon AWS, heard 100% since the program started
Cons:
- No internship, must take a summer semester in order to complete 4 semesters in 1.5 years
- Bad location, Pittsburgh, not like NYC or bay area
- Significant internal competition, so many talented programmers, 1000+ CS masters applying for similar jobs every year
- Not a popular program, the program is originally designed for cybersecurity, not a traditional CS/DS program, though it turns out to be flexible
- Generally new and small, no public stats on placements and salaries etc.
- Not so well known as Berkeley in non IT-related fields
- Lack of help in job search, basically just LeetCoding, resume, coding tests, interviews, etc.
Berkeley MFE
Pros:
- A traditional MFE program with stable historical placement data
- Good placement numbers, at least up till now
- Responsible program director and great career services
- High bar in admission, admitted students seem to have very outstanding background
- Good program reputation, and good school title
- Good location, near bay area
- A 12-week internship covered (most likely)
- Target on obtaining a quant job
- Network resources, alumni, fellow students, professors, lecturers etc.
Cons:
- An MFE program in a business school, courses are mostly finance-related, technical courses (required to complete online) are not taught on campus
- Probably unlikely to learn very technical things, like ML/CS/Systems/Software, as in CMU SCS
- Knowledge taught in traditional MFE programs are becoming more and more esoteric and useless
- Most likely to be placed in banks, still needs strong individual Math/CS abilities to land a job in buy-side
I'd really appreciate it if someone could give me some suggestions on career path and the current situation in the quant industry. Thank you!!!