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NYU Tandon School of Engineering - MS in Financial Engineering

Bridging Financial Theory and Practice

  1. Carmen Montes de Oca
    Established:
    1995
    Type:
    Full-Time and Part-Time
    Tuition:
    $54,318 (Total cost of program including tuition and fees based on 2016-2017 rates)
    Location:
    Brooklyn, NY
    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 at the Department of Finance and Risk Engineering was the second program of its kind anywhere. The MS in Financial Engineering program furnishes students with foundational knowledge in financial concepts. This knowledge then becomes a springboard to specialized fields where students can apply concepts to everything from derivatives risk finance to financial IT and algorithmic trading on Big Data.

    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 as well as GRE test scores. When applicable, applicants must also demonstrate English language proficiency to be determined by the TOEFL score.

    FALL 2016 ADMITTED STUDENTS PROFILE
    New students enrolled: 146
    Average undergraduate GPA: 3.84
    Average Quant GRE score*: 169.3

    *GRE score on the new 130 – 170 scale

    CURRICULUM
    The program requires 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)
    • Track-required courses (7.5 credits)*
    • 1 applied lab (1.5 credits)
    • 4 elective courses (6 credits)
    • Capstone experience (3 credits)
    • Bloomberg Markets Concepts certification (0 credit)
    Students follow one of four different tracks as they earn their degree:
    • 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.

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

Recent Reviews

  1. Anonymous
    Anonymous
    5/5,
    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.
  2. Anonymous
    Anonymous
    1/5,
    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.
  3. nobody
    nobody
    4/5,
    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.
  4. Anonymous
    Anonymous
    5/5,
    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.
  5. Anonymous
    Anonymous
    4/5,
    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.
  6. Anonymous
    Anonymous
    4/5,
    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.
  7. Anonymous
    Anonymous
    4/5,
    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.
  8. Iriss
    Iriss
    5/5,
    I am recently graduated from NYU Tandon, and I would like to share some point of views.
    Pros of the program:
    1. The program has four tracks, and the curriculum is well diversified, so you are free to choose the classes and areas you are interested in. Mostly, I took courses related to quantitative finance, covering area like stochastic calculus, numeric methods, asset pricing, programming labs, etc. And they are adding some new courses each semester.
    2. There are many great professors in the program. I took classes from Agnes Tourin, Andrew Papanicolaou, Song Tang and so on. Their lessons covered useful knowledge needed in quantitative finance. Also, they are very responsible and kind to help and answer my questions.
    3. The program has a new placement director Sara Tomeo before I graduated. She is very resourceful and experienced. She shares many information and opportunities about internship and full-time jobs.
    Cons of the program:
    1. Since the program has four tracks, and the curriculum is diversified, it might not be enough if you want to focus on a specific area. Also, there are not many math courses, so you have to choose from other departments.
    In conclusion, I think the program is improving.
  9. jpiral
    jpiral
    4/5,
    I am May2016 graduate. It is very positive for me to take this program. The full-time prof.s are responsible for their students, not to mention being kind. I was very thankful to get every response from my every question via email. I chose my courses depending on my capability and interest. Therefore, they were effective and efficient for me to learn. Since there are ample supplies of knowledge in each course, being highly motivated is helpful. Or I would like to say "being interested". Prof.s' notes are extremely useful for understanding new concepts and for exams. The more I read, the better gist I got. On the other hand, part-time prof.s have different styles. Some would give presentations on class and some focus more on practice. I gained a lot from those courses. They trained me to be a qualified financial engineer. For some minor points, there might some culture shocks among students, which challenged us in every aspect of study and career. There were four tracks to choose and we could also customise our own depending on what kind of job we want to do. The new department chair has arrived after I graduate. I truly want to take one or two courses of him or other new interesting courses. I feel thankful for taking such great program in my life.
  10. Anonymous
    Anonymous
    5/5,
    I am a currently enrolled student. I would like to share some views.
    Pros.
    1, Ever since Peter Carr came to Tandon, he keeps inviting people with industry experience came to teach lessons, like Edith Mandel, Pierre-Yves Guillo etc.
    2, New placement director Sara is resourceful and experienced. She keeps us informed with multiple internship / full time job opportunities which is hard to find in internet. Many students have found internship this year with the help of Sara.
    3, Some professors have amazing teaching skills which explain widely regarded complex knowledge in a very understandable way. Especially Prof. Tang’s C++ class.
    4, Classmates are talented. Again, since Peter Carr joined us, the admission becomes more selective. Most students from China are from ‘985’ or ‘211’ university with background like mathematic, physics, computer science, etc. Students from Tsinghua, Peking, Fudan and SJTU are common seen here.
    Cons.
    1, Like most programs, there are some curriculums which are too theoretical.
    2, It’s a traditional MFE program with traditional curriculums. Personally speaking, it would be better if more Data-Science related courses were added. Like Hadoop, Storm and Spark etc.

    In conclusion, the program is rising. Welcome aboard.