Columbia University - Masters in Financial Engineering

Academics:

Core topics include optimization, stochastic models, statistics/time series, monte carlo, financial engineering / options pricing. The program had real professors (research, tenure track) teaching most of the core classes which was good. From the core courses, I thought statistical analysis taught by Professor Agostino Capponi was well structured. It gave a good balance between rigor, for understanding the theory, and just knowing, for application purposes. Professor Capponi is a great teacher as well. Unfortunately there were some professors who didn't seem to care enough. A lot of courses were not well structured nor carefully treated, resulting in a poor learning experience and not a real understanding of the material. Perhaps due to the relatively diverse educational backgrounds of the students in the program, they cannot develop the subjects more rigorously. Some classes were just speeding through lecture notes to cover the topics. Because of this, don't expect to get an understanding of how to think about problems which you haven't already seen before. Many students have already learned the core subjects, so they have an advantage when it comes to the tests, as it should be since it's only fair. But the poor course structure and teaching only increases the disparity in exam grades, which I believe is a problem, particularly so with regards to difficult tests in topics like SDEs, stochastic calculus, stochastic integration.

You need 36 credits to graduate. The core is 18 credits. There is a list of pre-approved electives (not the one on the program website) and you can also apply to get a course not on list approved as an elective. They are relatively lenient with what gets approved, as long as it is somewhat relevant and quantitative / analytical. I'm not sure how unique this is to this program, but I was still really appreciative of the opportunity to have classes outside of the program or even from other departments.

Students:

Some students were caught cheating by having the solutions to a final exam beforehand. Not sure how that happened. There are a lot of smart students though, and I think most are pretty nice people.

Practitioner Seminar:

The talks based on industry research papers were too complicated and most people got nothing out of it. I didn't like the fact that there was a required 500 word reflection after every seminar, it doesn't create the right incentives.

Career Prospects:

A lot of students have struggled to get summer internships. Career services is generic and not specialized. They use AI to grade your resume. Basically don't expect them to place you into a job with connections, you need to do it yourself. You may see some decent placements come out from the program but it's not the program that elevated them to that position. They were already at that level and they came for the brand name / visa. MFE programs in general will not place you into HFT, prop trading, buy side quant research, etc. If that is your only goal, there are better ways to achieve it.

Program / Department:

One cannot ignore the fact that the IEOR department runs 5 MS programs in their department totaling ~800 people per graduating class. That's a lot of people with very similar degrees competing for jobs. That means each student and program loses its value and it would suggest that the department does not care about the MFE nor any of the other 4 programs.

If you are an international student who just needs a visa, this is probably a good pick for you. Otherwise, I would probably look at other programs, including those outside of MFE/FinMath programs .

1. Admission Process:
Columbia's MSFE was one of a handful of programs I applied to. The application was fairly standard (grades, experience, scores, essays, etc.) and the decision came back around mid-February which was ahead of most of the other responses.

2. Courses/Instruction Quality:
I think instruction quality could be greatly improved. Some professors were amazing while others skimmed the material, seeming to assume that we knew everything already. One thing to note is that much of the material is extremely theoretical, and so independent study is necessary to see how a lot of it can actually be applied. The material is very difficult as well, and I will say that most classes are graded on a curve, so don't freak out if you "fail" a test. For example, my overall grade in one class was a 59% and that came out to a B+.

All that being said, I think the classes are a great way to tell if you want to be in the industry. I had a difficult time with the material, but knew I wanted to pursue this path when I realized that I loved doing it anyway. The professors are smart and able to answer any questions you have, and I really feel like a whole new world of information was opened up to me through this program. I also feel like it pushed me to learn "how to learn" and increased my curiosity.

3. Career Services:
In this section, I can't say much. When I visited career services I got some guidance about how to write better bullets on my resume, but I didn't get much beyond that. I went again to ask about how to be better when looking for a job or networking and was basically told to keep doing what I was doing. Friends in the program told me they got the same thing.

I would also mention that every other week there are speakers from the industry that come to talk about what they do at work. One speaker in particular inspired me and I tried multiple ways to get in contact to learn more, but got nothing back. This experience was eye-opening for me and I think it would be accurate to say that unless you're a top student or unique in some other way, you're pretty much on your own when it comes to career matters.

4. Overall:
Overall I loved the material of the program and realize I needed it to learn more about this sector of finance. However, as a middle-of-the-pack student, it felt like I was a bit worthless in the eyes of the professors and admin.

5. Misc:
If you join this program, make sure to start networking with anyone and everyone you can as soon as you get the decision. Also make sure to start studying things like the green book and applying to internships/jobs as soon as possible so you have the best chance of finding something.

1. Career service with advanced AI techniques (tutors will use chatgpt to edit your resume)
2. Fast-selling career events, tickets are often sold out very quickly and no spot is reserved for FE (real target) students
3. Some professors' lectures (core module) are like bringing me back to my childhood. (Poor lectures, terrible recordings, poor notes, vague definitions and hard questions)
4. More opportunities to be with your family after graduation. Lower employment rate compared to other Top quant programs means you have to go back to your mother country.