NYU Tandon School of Engineering - MS in Financial Engineering

NYU Tandon School of Engineering - MS in Financial Engineering

Bridging Financial Theory and Practice

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Location
Brooklyn, NY 11201
Application deadline
Feb 15
At the NYU Tandon School of Engineering, we train our students to do exactly that: to engineer the future of finance and transform financial theory into practice. Launched in 1995, the MS in Financial Engineering (MSFE) at the Department of Finance and Risk Engineering (FRE) was the first curriculum to be certified by the International Association for Quantitive Finance (IAQF). As one of the largest and most prestigious financial engineering programs, we expand conventional financial engineering to encompass technology and innovation, including artificial intelligence, machine learning, blockchain/cryptocurrencies, and data science. Our international reach creates opportunities for partnerships with the most renowned universities, professors, and institutions from around the world.

ADMISSIONS
The Department receives a large number of applications every year. To be considered for admission into the MS in Financial Engineering program, students must have a Bachelor’s Degree from an accredited institution and proven mathematical proficiency in:
  • Linear Algebra
  • Probability Theory
  • Calculus
  • Applied Statistics
  • Computer Programming
Applicants must submit official transcripts from each institution attended. When applicable, applicants must also demonstrate English language proficiency to be determined by the TOEFL score.

CURRICULUM
The program requires the completion of 33 credits to qualify for graduation. FRE offers over 80 courses, taught by faculty with extensive practical expertise, who produce world-class research while teaching both introductory and advanced courses in a small class setting.

To earn a Master of Science in Financial Engineering, students must complete 33 credits to qualify for graduation, as follows:
  • 5 core courses (15 credits)
  • Focus area and general elective courses within FRE and closely related fields personalized by the student, totaling 13.5 credits
  • 1 applied lab (1.5 credits)
  • Capstone experience (3 credits)
  • Capstone assessment (0 credits)
  • Bloomberg Markets Concepts certification (0 credit)
The program allows students to select courses from the following focus areas:
  • Financial Markets and Corporate Finance
  • Computational Finance
  • Technology and Algorithmic Finance
  • Risk Finance
There are four types of Capstone experiences: theses, projects, special topics, and internships. Projects can be done with industry advisors.

PROGRAM FEATURES
Pre-Program Boot Camp: In order to help incoming students reach their maximum potential, the FRE department provides a comprehensive two-part pre-program boot camp every summer. The boot camp consists of an optional six-week online course in early summer, and a mandatory two-week intensive program on campus in August prior to the start of the Fall semester. Covered topics include Capital Markets, Advanced Calculus, Linear Algebra, Python Programming, Probability, Statistics & Risk Management.

The boot camp’s purpose is to prepare incoming students for the interview process that will begin soon after the start of the Fall semester. The top financial firms recruit in October for quantitative internships beginning in June of the following year. The boot camp evaluates students on a pass/fail basis, but the perspective gained is invaluable for gaining an overall understanding of firms' expectations of job candidates coming from an engineering school. The types of questions asked by interviewers are broad, ranging from mathematical brain teasers to technical programming questions involving machine learning and artificial intelligence. Candidates may also be asked to take written exams with questions on stochastic calculus, Black-Scholes theory, or Python coding. There is a lot to know, and few people (if anyone) have mastered it all, but attending the boot camp is the fastest way to become familiar with the landscape of topics important to the modern financial services industry.

Customized Educational Experience: NYU Tandon MSFE students have the flexibility to tailor their academic and professional focus in a way that best suits their interests and backgrounds. The Tandon MSFE is not a “one-size-fits-all” program, and is proud to have graduates beginning their careers in a range of functions within the industry; from Traders to Desk Quants, Risk Analysts, Software Developers, and beyond.

Large Course Offering: Over 50 department-specific courses are offered to the Tandon MSFE students each semester.

Small Class Sizes: The average class size is around 15 students, and no classes are larger than 30.

MSFE Career Guidance: In addition to the resources provided by the university-wide NYU Wasserman Career Center MSFE students have the benefit of receiving career support through the in-house FRE Department Career Resources as well. From FRE alumni networking events to recruiting presentations, resume reviews, and mock interviews; there is no shortage of resources available to students in the program. The FRE Career Placement Director works closely with students in the program to provide the resources and guidance they need to succeed.

Weekly Seminars with Industry Practitioners: Students are exposed to industry practitioners through the Peter Carr Brooklyn Quant Experience (BQE) Seminar Series, as well as talks provided via program partnerships, such as the Quantitative Finance Weekly Seminar.

Industry Connectivity: For the Tandon MSFE, integration with industry is not just a “nice to have,” it’s a “must-have.” Between 2016 and 2020, 40 new professors were brought on board from the industry, and that number continues to grow. The program is constantly evolving and adapting to the ever-changing climate of the industry and markets.

For more information, please visit the program's website:
Finance and Risk Engineering

Stay up-to-date with department news whether on the go or at your desk. Follow FRE on LinkedIn, Twitter, Instagram, Facebook, and YouTube.
2025 Ranking Data
Rank
9
Total Score
77
Peer Score
3.0
% Employed at Graduation
67%
% Employed at 3 months
89%
% Employed in the US
64%
Compensation
$119,528
Cohort Size
146 FT
Acceptance Rate
28.1%
Yield Rate
31.8%
Tuition
$81,581

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46,835
First release
Last update

Ratings

3.43 star(s) 30 reviews 3.50 star(s) Students Quality 3.50 star(s) Courses/Instructors 4.00 star(s) Career Services
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Latest reviews
Headline
Amazing Career Service
NYU FRE has the best career service! The program is somehow designed for preparing for work, which I really need.

During the Bootcamp, we work on technique interview related questions with professors. And we are asked to attend career workshop before the first semester, which is highly helpful for international students to understand how to find a job in US.

Sara, our career advisor, is super professional and sweet. Whenever I have career related question that bothers me for a long time, she can always help me out! Also, we have proficient resources for job hunting, including mock interview (both behavioral with Sara and technique with alumnus) , career workshops, templates of CV/cover letter/thank you letter. She also organized us to prepare for interview questions for share. I was impressed by the time when I made a mock interview appointment on Friday, and I was reached out by an alumni in only several hours. So efficient! Our alumnus are also super helpful and they are willing to share!

Feel proud of FRE!
Recommend
Yes, I would recommend this program
Students Quality
5.00 star(s)
Courses/Instructors
5.00 star(s)
Career Services
5.00 star(s)
Upvote 2 Downvote
A
Headline
Research before you join
I am a current first year student in the program and so far my experience with the program has been bad (being generous). The thing which the program advertises the most is large cohort, small class sizes, industry profs and large number of courses to choose from.
1. Large cohort and small class sizes: the obvious problem with this is that if there is a course which is high in demand, only 30 (or 20 in some cases) people will get it. There maybe multiple sections to the course but the content will vary vastly from one prof to another with one prof ending the course at risk neutral pricing and the other doing stochastic modelling. The course syllabus given is mainly for reference and most of the professors just mention what some approach or model is rather than going through the mechanics and helping us build intuition. You can google 10 different topic names and read the first page of the topic and be done with the course. In addition, the admissions criteria for the program is set very low and people with little to no background in either math or finance end up in the program which drives the stats lower. The cohort would be the most average cohort you can get.
2. Industry profs: the thing about industry profs is that most of them are very disconnected from how one should teach and structure the course. Most of the courses taken by them are 1.5 unit course (half semester) and the courses are very rushed with majority of them not completing the syllabus. A few of the profs don’t even have a syllabus but would teach topics what they feel like teaching. I am enrolling in the program to learn the concepts and build a toolkit, teaching some tips and tricks for on the job work will not help me clear interviews and every firm has different code base so majority of what you are teaching might not even be relevant. (Although there are some very good profs like prof. Tang, Adams, Mandel)
3. Large number of courses: Most of the courses are overlapping with each other and when asked for recommendation on what to take from the department the usual answer is choose what you want. In addition, as I pointed out earlier that majority of the courses are half semester courses, you just end up learning the jargon of the courses without building any skills. I am in my second semester with 12 credits remaining and can hardly fill it with 6 credits of acceptable courses for the next year.
The career service of the department is also bare minimum. There are no networking events organized and very few job postings (although LinkedIn has much more). I have gained much more valuable information by following Ashley Cross on LinkedIn (CMU’s career advisor) than my career department.
Advice to incoming students: Select your courses carefully and take advice from seniors on what courses to take. Start networking and preparing for interview from the day you receive admit. And lastly hope that we get a new program director who is decisive and can improve the program.
Recommend
No, I would not recommend this program
Students Quality
2.00 star(s)
Courses/Instructors
2.00 star(s)
Career Services
3.00 star(s)
Upvote 2 Downvote
M
I would like to share a few things for incoming or prospective NYU MFE students!

1. We have a large number of courses you can choose from for each semester, like machine learning, derivatives pricing, risk, quantitative trading, portfolio management... I want make it more specific, for machine learning, we have different courses like Machine Learning for Finance, Advanced Machine Learning, News Analysis.... If you like trading, we have Algorithmic and High Frequency Trading, Active Portfolio Management, Fixed Income Quantitative Trading, Quantitative Trading Strategies, Quantitative Equity Investment, and etc. I believe you will find the courses you like! These courses are all taught by professors from industry with senior title.

2. We have two Career Websites. One is by NYU, the other one is by MFE department. Most of the time, we use our department career net. Our career replacement director, Sara, is the most helpful career director I have ever met. She organizes many on-campus recruiting events for our students, post many "only for NYU MFE student" jobs, provides helps from resume to interviews, literally, everything. She is not only helping you with job findings, but also "pushing" you to find a job. If you do not apply jobs through MFE career net, she would send you an email to understand why and she would be more than willing to help you with any problems! She even contacted many international companies, like securities company and funds in China to give more opportunities to students who want to work outside US.

3. The third one is for students who would like to apply for PhD in the future. As we all know, most of students get a MFE degree and then go to the industry. But it is not uncommon that MFE students in our department decide to pursue a PhD. We have capstone research projects, thesis, industry research opportunities, and other research opportunities which can equip you with a strong research ability. I really appreciate Professor Carr's time and helps! It was an honor to be his student! He helped me with everything regarding my PhD application. For this semester, he is working with 4 students who apply for PhD. We all got offers, like Johns Hopkins University, NYU Courant, University of California, Santa Barbara, Boston University, and University of Utah. Without Professor Carr's help, we could not even make this happen! So I would say, our department is not only helping students get into industry, but also providing numerous helps to students who want to get a PhD!
Upvote 1 Downvote
I would like to share my experience not as a NYU MS FRE student but as a NYU Tandon School of Engineering international grad MS student from another program. Last 2017 Spring semester I took Corporate Finance at the FRE Department, it was a really great course that I highly recommend, the Professor is a master on the topic and with tons of practical experience of real cases and advisory experience to financial institutions around the world, he taught us how to really apply financial thinking and tools to real cases and CFO's challenges.
I believe important to share this really positive experience, as a student who is trying to pursue a career on investment banking and project finance, I am convinced that through the practical expertise taught at the NYU FRE Department students are really wining what we should be looking from our graduate experience, real world tools and skills in order to succeed on our future careers.
Upvote -2 Downvote
It's so funny that everyone wants Peter Carr to carry the whole department. Everyone has only one answer to all the problems - "we have Peter Carr". Also, it is so obvious from the reviews getting deleted that there's something seriously wrong with the department. It's a scam running for past couple of years under the name of NYU. Don't try to make a fool out of everyone by writing fake reviews. Peter himself knows the truth. Below is a detailed review -

1. If you want to be honest and work hard - you'll fail terribly because most of the students will cheat off their exams and get good grades.
2. Some professors do not really want to teach and it seems they're doing a favour by coming to the school.
3. No career help from anyone here are at the department. Believe me it's a scam.
4. This program is not for anyone who aspires to become a quant.

And lastly why are all the good reviews coming up now? Good marketing campaign. Mixing up education and money. Job well done.
Upvote 2 Downvote
N
This is the third edition of my comment. Try to be more objective.
1. In response to some comments below, I appreciate some of their ideas, which helps me to suggest Peter on how to improve our program.
2. For others, I have to say that any program will never guarantee you any job placement. It’s not like you paid the department 60k USD and a red carpet will appear automatically to lead you to Wall Street. You have to work hard. Some people have already land great jobs in quant or other fields. If you don’t know any of them, then it is your problem. If any jobs other than a quant is not “placement”, then there will be far less employment records in other programs as well.
3. To the so-called “professor”, I wish you can present any evidence, or simple pay us to create “evidence”.
4. To the guy who claimed that many recruiters refuse to take our resumes, please name them, or their companies so you claim will be more compelling, and we can save time avoiding these teams. Please. Please.

True, the department is collecting students’ reviews to bring more changes to the program, but it is not a marketing campaign trying to furnish our reputation. I have sat with Peter and spent a few hours to discuss my experience so far in this program, and how he can improve it.

I’m here to express my own opinion, not to flatter, not to slander. I appreciate what the program has brought to me (quant skills, access to great resources, scholarships, etc.), and I dislike some other aspect (some professors’ accent and attitude, delays in some daily operations). That’s why I’m sharing my experience and giving 4 stars instead of 5, while I know some guys genuinely want to contribute nothing other than 0 stars (but sadly, they can’t give 0).

The program is rising from mediocre, with the help of some talented and determined people. This summer (2017) the incoming students are taking an online boot camp. I’m sure they will be better prepared for internship application and interviews. I’m very happy that in less than a month Peter have put what we have discussed into action. He loves this program.

My thoughts are presented as follows:

What were your favorite courses and instructors?

I regard Prof. Jerzy Pawlowski (R and Algorithmic Portfolio Management), Prof. Tang (Financial Computing and Big Data Analytics), Professor Mandel (Fixed income quant trading) as the best instructors of this program. Be sure not to miss their courses.

What courses are missing?

For courses, I would like to have Python, machine learning course (Peter had a new professor and he will open this course in Fall), maybe deep learning. It will be great if we can organize our students to test strategies on open platforms like Quantopia.

What would you improve in the program?

Some advice from faculty members are very helpful, like joining meetups. We can make the advice into 0 credit courses to push students into learning things.

How would you improve the job placement process?

The job placement process is hard to take off quickly. We had an awesome director, but she will not provide job offers to all of us outright. We need to focus on two parts: job application and interview. She is working very hard at the job application side, and we need to improve the interview side, like using Financial club to organize interview training/peer interview sessions.

At the very end, I would like to notice anyone who will be reading this review: all reviews are subject to everybody’s very own experience. As time passed by, and as the situation changes, some of these reviews may not be valid anymore. Take our words with care.
Upvote 1 Downvote
Currently student here. Someone asks to name some students who go to bb. Here is the situation. We have Barclays Capital, Goldman Sachs, Moore Capital, JPM. That's just what i have known so far.

About the courses, i would say some of them are great and some of them are easy.
Programming: Financial Computing(C++), great course taught by great professor. Algo Portfolio Management, which requires high level R language and relevant portfolio knowledge. Fixed Income Quantitative Trading, use python to write trading strategy.
Math: Stochastic, Continuous time finance are really great and important course for quant.(btw, CTF is taught by Peter)

This program is definitely in progress since peter came here and we got a lot of opportunities in career. And recently Sarah was invited to be our career mentor who was responsible for campus recruiting at Morgan Stanley.

I would say it's a great program overall.
Upvote 1 Downvote
I graduated from this program in May 2016 and right now work in Susquehanna International Group after I left Soc Gen.

The overall experience in the program is positive.

I am quite disappointed by those 1 star/ harsh reviews below. Especially the people who blame this department did not place them with a job. My suggestion is that If you really want a job, then go talk to people, go networking, go prep for the interviews, go find internship, read more books at home. No such program is going to spoon fed you and make sure you have a job right after you graduate.


Pro:
Recommendation of professors:

1. Professor Hoff (commodity ) : super nice and knowledgeable, his lecture is divided into 2 part, first half is industry insight and second half is the Math.
2. Professor Pawlowski (R, Algo portfolio) : everything you need to know in R related to Finance and quant trading. His lecture is really useful, I share it with my colleague and having traders and quant using this as template of our code.
3. Professor Mandel: Cover fixed income in solid and practical, it is the kind of knowledge you need before you join a fixed income trading desk.
4. Professor Tang: C++, great teacher, teach the material well. A good refresh for student who already know basic data structure and fundamental object oriented programming.


Overall the courses are great except Accounting(useful for Credit trading and Equity trading) but now accounting has been cancel which is a good thing.

Since this program has so many courses to choose from, it would be helpful that you ask yourself what you plan to get out of it after 2 years right from the beginning and build your profile and chose courses according to that goal. (Technology, Quant strategist, market risk management or quant trading)

Great location, just being in New York is a big plus for such program like Financial Engineering. This mean lot more job opportunity and the classes are more practical.

Small Class size, even the program is big but the student in each class is around 20

Lots of industry professors, so you have a good idea of what is going on in the street.

With Peter Carr being our new Department Chair, he restructure this program and already brought in talented industry professors from the street and initiated industry projects with companies. Also, Sara new Career Placement Director and she did a great job in reaching out to company and alumni to assist with placement.


Con:
1.5 credit course( 7 lecture) seems too short. Could restricted such that 2 professor teach one topic like in Courant.

Need one python classes. You can learn at home, but would be a great idea to structure the class around Python or R.

More courses on fundamental Statistic, probability theory, and Stochastic Calculus, even it is listed as requirement but students come from different background.

Cheating in the class should be punished more severely.
Upvote 1 Downvote
I am a Fall 2016 student in NYU Tandon's FRE program. Overall, my experience has been pretty good... academics (including the coursework, professors) are good. Yes, few professors/courses might need some tune up, but there in multiple course offerings by different professors which can be pursued.

The career cell at NYU performs satisfactorily however it can do better. Sarah, the new placement director at FRE is doing the best she can considering the uncertainty in the job market (especially for International students, which is 99%+ of the enrolled students)

If you build your profile well, take the right courses (according to your interests), put effort in your academic projects, I don't think there is a downfall to the experience.

Recommendations for Negative Reviewers:
1) Don't expect to be spoon fed all the way through the program. No one can cover 100% of the stuff in class. I have seen people crib that they could not correctly answer a question in an interview and blame that it was not covered in class. (Thats just total BS). If you are gonna blame someone ....blame yourself for not cracking the interview.

2) No program will promise you a job at graduation. If you want a job you will need to get go out and get it....Applying through portals only gets you upto a certain point...

3) Most skills are picked up in Finance are OTJ. If you are looking for an entry level job, the chances are you will be interviewed on your academics (mostly basics). If you know your stuff, you will sail through..... There is difference between academic knowledge and industry practice.... you will know it once you enter the industry.


Recommendations for the Program:
1) Scrap the 1.5 credit courses: I don't think there should be any course with 1.5 credits.... You can make the syllabus more detailed and make them 3 credits. Personally, I don't think 1.5 credits does justice to any subject.
2) The program size is too big: I mean 150+ students (you must be kidding me). Most programs on an average have 60-80 students graduating each year. Its difficult to place that many students in a year (no matter how high the quality of students you have... which is not the best anyways).
3) Faculty: Please review the faculty, ...I have personally not faced any issues like any of the comments below but I guess they are far too many to be ignored.

Overall, the program can be a home run or a strike out but it depends more on the student and less on the academic program/department/faculty... yes they are always to guide and help you out in case of questions. The program is undergoing major changes in terms of coursework as well as the faculty, Peter Carr is making changes which I feel will move the program in the right direction.
Upvote 1 Downvote
I recently graduated from NYU Tandon, so I would like to share my opinions about this program.

Pros:
1. Although we have more than 100 students in this program, the size of classes is small. The limit of the class is 30 students, which means we have more classes. The classes are diversified enough to cover the most business that investment bankings are doing. 80 percentage of the classes are offered both in spring semester and fall semester.
2. There are some financial classes offered. If you are not familiar with finance, it is a good chance to choose them. Otherwise, you will be able to waive them.
3. NYU has a powerful career service. NYU CareerNet is a very convenient and useful website to apply for internships and jobs. Many students got their internships and full-time jobs through that. Besides, Sara, the new placement director has provided us a lot of information since she went to our program in Feb. As far as I know, some students got full-time quant or risk jobs at J.P Morgan, Societe Generale, RBC Capital Markets, Citi Group. Some students interned at J.P Morgan, Barclays, Goldman Sachs.
4. New department chair Peter Carr tried to improve the program. He hires a lot of professors working in the street. New courses such as Machine Learning, will be introduced in the next semester.

Cons:
1. The final exams of some courses are kind of too easy, so some students can get relatively high scores by merely practicing the sample exam even if they may not have a thorough understanding of the courses.
2. Most of the professors are not as famous as professors teaching at Courant's Mathematics in Finance Program.
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