Latest reviews

The following review is subjective and is most useful for students aiming to seek employment in the U.S.

Courses:
The program offers great flexibility, and professors are generally very nice. What you gain will largely depend on the courses you choose and how seriously you engage with them. Keep in mind that most courses may not directly help you during job interviews, but they can be valuable for building your knowledge base.

Career Services:
Resume drops can give you more exposure to employers, but whether you ultimately get interviews or offers depends heavily on your own background and skills. Some students get interviews from resume drops, and some don’t. Do not expect too much from career services.

Job seeking:
Employment statistics don’t guarantee anything. You could end up in either the numerator or the denominator of that employment rate. If your goal is to work in the U.S., you will need to figure out your own strategy based on your background. I would give the program a neutral rating in this regard. The program provides a reputable name on your resume, some industry connections through alumni, and a valid U.S. visa with work authorization if you are an international student. However, it is a highly autonomous program, and your outcomes depend largely on your own efforts.
This is a decent program for students with strong backgrounds, self-awareness, and determination. Nothing much to praise, nothing much to complain. In other words, it gives you a chance to be seen by Wall Street, but you will likely have to learn how to stand out on your own.

Other notes:
For those want to experience nature and country-life, Ithaca has its beauty.

The Master’s in Financial Engineering program at Lehigh is a strong, well-designed program that prepares students for a career in quantitative finance. The courses are flexible and focus on cs, statistics and finance.
This program will provide students capstone projects to work on quant related, hands-on project. Students get to work directly with industry sponsors, making the experience feel real and relevant.
Networking is also a major part of the program. There are plenty of events, guest talks, career panels, and conference that make it easy to meet alumni and professionals. These activities are especially important for me. They give me a chance to practice communication, build confidence, and improve my social skills.

The Master’s in Financial Engineering program at Lehigh is an outstanding program that fully equips students to succeed in a career in quantitative finance. In addition to its rigorous coursework, the program emphasizes hands-on project experience, allowing students to collaborate with industry sponsors throughout the duration of their studies. Networking is also a central component, giving students ample opportunities to showcase their skills to industry professionals. Overall, the environment is incredibly supportive, the coursework is on par with top programs, and what truly sets Lehigh apart is its exceptional project-based learning and industry engagement.

My experience at Fordham University has been deeply rewarding, both academically and personally. The curriculum—particularly within the quantitative finance and analytics disciplines—strikes a thoughtful balance between theoretical rigor and practical application. Courses are structured to push students beyond formulaic understanding, encouraging critical thinking, technical precision, and the ability to translate complex models into real-world decision-making. This approach has been instrumental in shaping my development as a quantitative professional.

The faculty at Fordham deserve special recognition. My professors—particularly Prof. Sheng—have consistently demonstrated exceptional mastery of their subjects, coupled with a sincere and enduring commitment to student success. Their guidance extended far beyond lectures—through office hours, project mentorship, and career advice, they fostered an environment where curiosity is met with encouragement and academic challenges become opportunities for growth. Their support has played a significant role in my confidence and progression throughout the program.

Equally impactful has been the community of fellow classmates. I have been fortunate to learn alongside peers who are driven, intellectually curious, and collaborative. Whether discussing derivative pricing, debugging code, or preparing for interviews, the shared motivation and mutual support within the cohort created an atmosphere that made even the most demanding coursework engaging and enjoyable.

Overall, Fordham University provided an enriching experience that strengthened both my technical skill set and professional maturity. I am grateful for the education, the mentorship, and the friendships formed during my time here.

Overall solid program

The cohort is very selective—students are smart, hardworking, and generally come from strong STEM backgrounds.

Academics:
The coursework provides a strong and relevant foundation in quantitative finance. It’s not overly career-driven like some other programs that tailor content toward interview prep, but the professors are professional, dedicated, and genuinely invested in teaching. You can learn a lot if you’re willing to put in the work. Some courseworks can get niche/too hard that it doesn’t help with your general job searches, so be careful with your course selection.

Career services:
This is where the program falls short. The career team doesn’t source many real opportunities; instead, they mostly host mandatory info sessions where company/ppl brand themselves, and students have mandatory follow-up essays to write to prove how much they “learnt”. I heard they improved a bit after my class’ graduation in 2023, I really hope they do. Most cohorts I know found their jobs on their own. The biggest career advantage is simply being in NYC, where networking and opportunities are more accessible.

Final Thoughts:
If you’re excited about quant finance, want to build a solid technical foundation, or just want to experience NYC, this program is a good choice. But be ready to push yourself through a lot of challenges—some meaningful, some not—and expect to drive your own job search. Being in NYC definitely helps if you know how to take advantage of it.

I earned my Quantitative Finance (QF) degree from Bayes Business School, and I would highly recommend it to anyone considering a career in finance or quantitative roles.
The courses that impressed me the most include:

Derivatives
Stochastic Calculus
Advanced Stochastic Processes
Simulation Techniques
Financial Modeling
Risk Management
Fixed Income

These modules are exceptionally well-structured and highly practical, especially when preparing for the job market. The modeling skills and techniques I learned during the program are widely applicable in my current role, both in theoretical aspects and practical implementation such as coding.
This degree not only helped me secure a job but also transformed my approach to problem-solving. Lecturers provide comprehensive notes, materials, and research papers, and they are always willing to give detailed explanations if you ask questions proactively. The program opens the door to the world of quantitative finance efficiently while leaving room for further academic pursuits, such as a PhD, if desired.

I’m a current MFE student (graduating May 2026) with a focus on energy. I came into the program from a finance undergrad with strong motivation but a clear need for deeper mathematical fundamentals, real research experience, and better industry access. After 1.5 years in the program, I’m very happy with my decision to come here. Below are what I consider the strongest aspects of the program, in order, though the lower points are not weak by any means.

1) Community & Culture

Beyond academic rigor, the professors genuinely care about your success and take a personal interest in helping you reach your goals. If you are proactive about your education, they respond exceptionally well -- guiding you toward the projects, topics, and skill sets that matter most for your career.

The cohort is also large and diverse. We are one of the largest across MFE programs ranked on QuantNet. You meet people with different backgrounds, strengths, and industry experiences. These classmates become your study partners, project teammates, and, eventually, part of your professional network. People here work extremely hard, and I’m confident I’ll stay in touch with many of them for years.

The programs administration team are equally supportive. They consistently approach student requests with a “How can we help this student get where they want to go?” mindset from the top down. Whether that means adjusting schedules to accommodate a job, helping with cross-registration, or advising on long-term career goals.

2) Academics & Research Opportunities

The curriculum is rigorous and flexible. Industry-practitioner faculty are extremely strong, and more excellent professors have been joining recently.

If you want deep theory, you can take multiple PhD-level classes that count toward the MFE. If you want practical quant research experience, opportunities are abundant.

You can also cross-register for courses across schools in NYU: Courant, Data Science, Stern, and others. This adds a huge amount of breadth and depth that many other MFEs simply don’t offer.

Importantly, the program is what you make of it. If you are genuinely passionate and actively involved in the subjects you came here to study, you will get enormous value. If you lose interest but still expect top outcomes, you might not have the same experience.

Many of the practitioner professors also go beyond teaching — they help students find internships, refer them for roles, and in some cases hire them for part-time or full-time work.

Professors who have made a particularly strong impact that I'd recommend students learn from are: Bouchouev, Ivan, Yao, Conklin, Shimko, Tang, Perry, Abousallah.

3) Careers

Career support is a real strength at Tandon, especially if you’re willing to put in effort and engage early.

Our careers director, Sara, works incredibly hard on behalf of the students. She supports networking, interview preparation, and overall positioning for competitive roles. The internal job portal she curates is excellent. Many of the strongest roles each year (hedge funds, banks, trading firms, quant/data science positions, and more) come through it.

I will be joining an oil major in their trading arm, which was a perfect match for my energy focus and research interests. I believe the program prepared me extremely well for this path.



The NYU Tandon MFE program rewards motivated, curious, proactive students. If you embrace the coursework, leverage the research ecosystem, and engage with the community, the return on investment is high.

I’m grateful I chose this program and would make the same decision again.

The course load is quite heavy, with about six or seven courses per semester, and the courses are generally more sell side or academic and It requires balancing academic studies with preparations for finding internships in the industry.
The program has an excellent reputation in Europe and a rich alumni network.Every week, some companies will give presentations, etc. (but they don't offer internal job openings).
Overall, the program is helpful for entering the industry, but in recent years it seems that the job resources it provides have been gradually decreasing. Most graduates still need to rely on their own preparation and applications, and the program doesn't offer much assistance upon graduation.

You get what you pay for. 95% of this course can be completed from home. Some of the Autumn modules results are based on an exam in summer that coiunts for 100% of the grade. Only 1 od the modules actually gives you "practical" assignments (only 2) that have anything to do with what a career in finance might entail. Its very theoretical. Some maths modules very difficult if you are not from a Maths/Physics background, the coding modules are basically "intor to Python/C++ 101". Two of the more interesting modules have had their lectureres replaced with TAs who cant even read the slides. This course is a massive disappointment and feels more like a few modules from different courses were thrown togetehr to create a degree. The Mathematical Finance MSc is much better and you might gain some knowledge/skills from that.

## Curriculum 4/5

The materials covered in the program are well-structured and comprehensive. It goes into details and deducts everything from the ground up. For example, for econometrics, I have utilized all linear regression techniques and time series models before I went to the program, but the class started from the derivation of OLS estimators and mathematical proofs. This approach helped me to understand the concepts more deeply and apply them more effectively in real-world scenarios.

However, I heard lots of students complained its too academic and theoretical, even with course projects, they still feel hard to connect the theories with real-world applications. Personally, I never find it hard to connect theories with applications, but I do agree that the program could benefit from more practical examples and case studies to bridge the gap between theory and practice.

## Delivery 2/5

Although I enjoyed the materials covered in the program, almost all class notes and slides are well-prepared and cover everything in details. But the delivery of some courses is not satisfactory.

I attended every class in person (mostly, LOL) and take notes carefully, I got full-gpa in the program, but I still feel like I self-studied half of the materials in some classes.

## Students 3/5

To be honest, student quality is not the best thing about Rutgers MQF. I maybe biased to say this, my batch is realitively strong compared to previous year and next year, we got several students from top undergrad programs, and I could see some smart and hardworking students in my batch.

But the standard deviation is huge. There are also students who basically do not care about the program, they barely study and cheat in exams!

The program is intense and demanding! The coursework is actually really heavy and tough, if you truely want to achieve a good gpa, you have to put in a lot of effort. But some students just just gpt through the program with minimum effort, they could still pass the classes, and give a impression that the program is extremely easy to pass (which is true for them). In short, its easy to pass, but hard to excel.

## Career Support 4/5

The career support provided by Rutgers MQF is decent. Some career events are not meeting my interests, but overall, the career services are helpful. Let's face the reality, in recent years, the competition for quant roles has become increasingly fierce, most of time you are relying on yourself, not the school, to land a good job.

I believe that the program has tried its best to provide career support, but ultimately, it's up to the students to leverage these resources and put in the effort to secure their desired positions.

## Summary

I truly believe I learned a lot from Rutgers MQF, the program has equipped me with a solid foundation in quantitative finance, and I feel more confident in my abilities to tackle complex financial problems. I would recommend this program to anyone looking to deepen their understanding of quantitative finance.

But at the same time, I put my effort to self-study and practice outside of the program, which I believe is essential for success in this field. And some students in the program may not share the same level of dedication, which can impact the overall learning environment.

If you are considering Rutgers MQF, I am sure you will benefit from it, but be prepared to put in the effort to make the most of the program.

I enjoyed the program very much and it definitely helped me transform my career opportunities. This program enables you to get a shot in quantitative finance, however it is not a given.

The program offer in itself is quite decent, however not all lecturers have the same quality of teaching. The people in the program are from multiple backgrounds which is nice and if you associate with the right people your chances of getting a proper job on the bayside are decent.

I gave career opportunities 3 stars, however I only went to one of the career fairs and never tried to use any other resources in this direction so I do not want to necessarily blame this on UCL.

Overall I'm was quite happy with the program, I'm grateful for the friends I could make, the things I could learn and last but not least the career opportunities it created for me.

A good broach into stochastic calculus for people that come from different backgrounds that are not necessarily in mathematics. However, weak overall preparation for the real world practicalities of pricing (i.e. Greeks are barely discussed, pricing exotics, numeraire, etc.). The course structure follows loosely on Steven Shreve’s books on Binomial and Continous-Time Asset Pricing. Nothing on the latest in the field of quantitative finance.

The C++ classes were impeccable and highly recommended as they brought me from absolute novice to intermediate and enabled me to practice good OOP development skills.

There’s decent instruction for many courses, but the course material is not the most rigorous to accommodate people’s varied backgrounds. Support for the master’s thesis is mixed, with some professors being very hands on, and others being absent.

Outcomes for the course are varied, some people were able to break into good quant roles, many were not.

Overall, for the current sticker price of the course, I wouldn’t necessarily recommend it, but if you receive some sort of bursary or scholarship from the university, and have a weaker background in mathematics— maybe consider. But the career outcomes are average, and it does not open any more doors than other MFin programs.

NB: I studied in Oxford between 2020 and 2021, mostly during the lockdown period. Therefore, my experience might be very different from the students in other years.

Lectures:
Most lectures are quite challenging, mainly because of the amount of content packed in such a short period of time. A lot of the time I found myself lost in the sea of lectures and coursework (and job searching) and forgot to really enjoy the subject itself.

The lectures are generally very math-heavy, yet maintain a strong finance background. A few stand-out lectures for me are Fixed Income and Credit, Stochastic Volatility and both C++ lectures. Ben and Michael are among the best lecturers with a deep understanding of the subject, intuitive explanations of the financial background, and clear math illustrations. Both C++ lecturers are knowledgeable and have different teaching styles, but both explain the subject very well with lots of examples. It's difficult to learn C++ just by reading the slides without practising, but they did a great job explaining some of the difficult concepts.

Most of our lectures are taught online due to covid, so it mostly feels like a one-sided knowledge transfer, rather than an engaging process with the lecturers and other students.

Exams and coursework:
The coursework and exams are quite difficult, especially those that involve proofs. The take-home exams for Statistics and Deep learning are fun but very stressful. For the open book written exams, the unfortunate thing is that they didn't balance the difficulty well. We had one very easy and one very difficult exam, so it basically became who could copy the most complete answers for the easy exam and not much to reference from the lecture notes for the difficult one.

Dissertation and industry placement:
We didn't have many companies recruiting interns that year, so only a small number of people went to do the industry placement. Most people did their dissertations with their professors; overall it's an interesting experience taking a small step into research.

Careers:
The programme has a big push for people to get a job upon completing the master. They will advise on your CV and help you apply for a few companies with which they have a collaboration. In my year, largely because of covid, we had only a few people who received a job offer immediately after the master, and a few others went on to pursue another master or took a gap year before pursuing a PhD.

Overall:
It's a very intense programme with many difficult lectures and exams, stress from interviews and job hunting and the uncertainty of your future. It offers a wide range of lectures that, even though you won't use all of them in the industry, give you a sense of almost all the quant areas, so you can choose what you like to start your career. And it helps the students get through the door of quant finance with the Oxford brand and internships. It would be better if you already had a clear plan of what you want to do after the master, either pursuing a PhD or going into the industry, so you could focus on preparing yourself alongside all the heavy study.

The courses and teachers were all great, but the career services office was truly exceptional. They helped students throughout the process with everything from finding and applying to internships to connecting students with former graduates at various employers. Their office set me up with an interview for the firm that I started working for after graduation

The Baruch MFE program has been an incredibly rewarding experience for me. One of the biggest strengths of the program is its career service. The career team is genuinely dedicated, extremely responsive, and provides very practical guidance tailored to each student. Their support throughout networking, interviews, and job placement has made a huge difference.

Another standout is Professor Dan Stefanica, who plays a central role in shaping the program. His mentorship, attention to detail, and commitment to students’ success create a learning environment where you feel supported both academically and professionally. It’s hard to overstate how much impact he has on the program’s quality.

Baruch also offers some truly enlightening and intellectually stimulating courses. Market Microstructure and Option Market Making are among my favorites — they are rigorous, hands-on, and provide insights that are directly relevant to real-world trading and quant roles. These classes changed the way I think about markets.

Finally, the alumni network is another major asset. Baruch MFE alumni are not only successful across the industry but also extremely willing to help current students. They answer questions, offer mock interviews, and give honest career advice — the sense of community is very real.

Overall, Baruch MFE is a program that pushes you, supports you, and connects you with people who genuinely care about your success. I’m very grateful to be part of it.

Strengths:

Tuition fees are low. While Switzerland is not the cheapest country, it is still possible to survive while spending slightly over 1k CHF a month, making it overall quite affordable, especially compared to many other master’s degrees in FE/QF.

ETH courses - there are many great courses covering a very broad range of topics. Courses themselves are taught well - instructors are world-class experts in what they teach and are passionate about sharing that knowledge with students. For courses which are not currently in the program’s official curriculum, it is possible to have them still recognised, provided that one can argue how they relate to quantitative finance.


Weaknesses:

Career services. Not overly impressive. Things get worse if you are non-EU, which makes it much harder to stay in CH after graduation. Most likely you will have better prospects in London. Nevertheless, I still think program’s graduates do well. It would be foolish to expect from any master’s program to send its alumni to JS/CitSec/HRT only. There are quant roles beyond OMM and with that in mind, given the geographical context, I think program’s alumni do fairly well on the job market, despite limited resources available from the program’s administration.

UZH courses - not very rigorous, not very useful. Unfortunately you can’t really structure your curriculum in a way that completely avoids taking them. Others have shared their thoughts on this aspect of the program and overall I agree with them.

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Also speaking of UZH, as it was mentioned, legally they will enrol you at UZH, which is quite unfortunate and makes it feel like the program is not really split 50-50 between ETH and UZH, despite being advertised as a joint program. But aside from this matter, I don’t think you will really feel that, seriously. Maybe it should be added that program’s diploma features both UZH and ETH as well as signatures of representatives of both universities. Applying for something like UK HPI visa (requiring to hold a diploma issued by a top50 university worldwide, which UZH isn’t) has no problems either - UK officials do recognise that ETH is one of the awarding institutions for this degree.

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Overall I think the strengths outweigh the weaknesses and it is still a very solid program to join. It is not very difficult to capitalise on its strengths, but for that one has to be clear about his or her goals when entering it.

Some modules were good and well taught, such as stochastic calculus and numerical methods in finance. However some were not well structured and the teaching was below average

The program gives some flexibility, with a fairly good choice of both core and elective courses, from ETH and UZH.

Core courses are extremely good at assessing minimum requirements, even if some of them are absolutely not «quant» at all (eg. Corporate Finance).

Elective courses span from rigorous mathematical finance, computer science, classical finance, excellent seminars, and finance courses without much useful content.

The admission process is extremely fair and there is a good mix of top students and second tier students.

Overall, I would recommend the course for someone with an economics, data science, statistics or engineering background. In my humble opinion, those with a mathematics (especially pure mathematics) or physics (especially theoretical physics), should opt for the ETH MSc in Applied Mathematics, as it allows to practically take almost every course in the QF MSc, without the requirement of taking many UZH financial theory/financial elective courses, which I found less interesting and well-taught compared to ETH courses.

Finally, applicants should be made aware of the fact that QF MSc students are *de facto* UZH students, without for example ETH cards/access to ETH buildings on Sundays, within the student association of UZH only (except upon special request), and are legally enrolled at the Faculty of Economics at UZH.

Since the MFE program is highly career-oriented, most applicants aim to secure strong job opportunities upon graduation. I will focus on the program’s career-support advantages:

1) Industry-aligned curriculum
The course structure closely mirrors real-world industry requirements. The program invites numerous practitioners from both the buy side (e.g., former portfolio managers at top hedge funds) and the sell side (e.g., MD-level quants, risk managers, and traders). The coursework is hands-on and project-driven, allowing students to build impressive, industry-relevant projects that significantly strengthen their résumés and improve their chances of receiving interviews.

Because many professors come directly from industry—and some even run their own firms—they frequently hire students as interns or even full-time employees. This direct access to industry practitioners is an invaluable advantage.

2) FRE Careers Technical Interview Mentorship Program
https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering/employment-outcome/fre-careers-technical-interview-mentorship-program

I am also one of the mentors in this program. We provide free one-on-one mock interviews and interview preparation sessions for students seeking summer internships or full-time positions. Each mentor specializes in one or two technical areas.

This mentoring program helps students avoid low-level mistakes and, more importantly, narrow down the scope of their interview preparation based on specific job targets. Most mentors have many years of industry experience. As interviewers, we have spoken with hundreds of candidates; as interviewees, we have gone through hundreds of interviews ourselves. This depth of experience is extremely valuable for students, especially those who are new to the U.S. and just beginning their career journey.

The University of Chicago Master in Finance has been one of the most rewarding academic experiences I’ve had. The community is tight from day one—pre-program events are intentional, people genuinely show up for each other, and I’ve made some of the closest friends I’ve ever had in such a short time. The sister MiM program has many events with MiF, so despite having a vastly different demographic there is actually alot of interconnectedness between the two programs socially which is great since this MS program feels less like a purely academic program but just overall reminiscent of undergrad with more focused recruiting efforts.
The curriculum is flexible. There are three core classes, and aside from Financial Accounting, the core finance requirements (Investments and Corporate Finance) are waivable, which gives you room to shape the program around your goals. You can also take PhD-level courses and one class from other MS programs (e.g., FinMath). That cap can feel limiting, but Booth’s faculty more than offsets it—this is a school with more Nobel laureates than anywhere else, and the teaching quality is simply better. Professors like Dacheng Xiu, Lars Hansen, and Stefan Nagel are operating at the frontier of finance, and having access to them is something you don’t get in most technical master’s programs.
Advisors are invested in students, but for quant recruiting specifically, you need to take ownership early. Prep starts well before the program kicks off, and that’s just the reality for anyone targeting top-tier quant roles. That said, Booth’s name opens doors everywhere. I received interviews across the top firms and ended up with pretty decent offers w comp around 150k annualized. The program is versatile: if you’re focused and know what you want, you can turn it into exactly what you need.
My advice to future students: come in ready to recruit. Use the Booth brand, lean on classmates, and reach out to current MiF students in quant—we have a growing group. I’m in the second cohort, so feel free to reach out as well.