University of Illinois Urbana Champaign - Master of Financial Engineering

The MSFE program is now led by professor Feng, who is the best director I have ever seen. I think most issues previously mentioned no longer seem to be a concern. While many enrolled students may not initially appear exceptional enough to secure top market positions, the program still provides equal/more opportunities to enter prestigious banks and hedge funds.

In the second semester, there is a practicum project where HR and R&D departments from top banks like JPMorgan Chase, Citibank, Goldman Sachs,etc.. give projects to students and guide them to achieve specific industry targets.(In our class there is 6 projects given by differnt companies) Four students from our class were hired directly by HRs from top companies immediately after completing the project. Please note that the job position was difficult to find than normal because of covid19, but they still did it. Such opportunities are very very rare in other colleges in my understanding.

For those bad reviewers: Before you criticize this program for not being good enough or having poor job placement rates, ask yourself why you weren't admitted to NYU, Baruch College, or any other "good" MSFE project. Is it because you didn't want to go? No, it's because you weren't good enough. Reflect on your own shortcomings. If you believe your abilities are on par with students from those top schools, this program offers you ample opportunities, or even more additional opportunities, to achieve your quantitative finance goal in your career plan.

I would rate the quality of students as 3 or 4 stars because you will have roughly 5-6 very good colleagues, but there are some poor students, like most ones who provided the negative review. I don't think that's an issue, at least for me 3-4 friend with excellent ability is sufficient for me. You are the master to decide where your future should go.

MSFE in UIUC has great course arrangement and the course has great improvement of my skills in quant, data analyst, risk modeling those field. Besides, the program has practicum which means intern opportunity provided by the program to work in practice situation and that opportunity may give return offer when you act perfectly impressed the company staff.

I’m a current student in MSFE, and I will graduate in December 2020. From my experience in UIUC, I believe the program provides a great opportunity for students who are seeking to make contributions in financial engineering industry but don’t have comprehensive knowledge on finance or computer science background. The curriculum setting is very helpful that includes various topics that follow the popular trend in financial industry. Such as risk management, derivative pricing, machine learning, and more relevant topics that many companies in financial industry focus on. MSFE provides essential knowledge in financial engineering, and the flexibility for students to explore their interests of specific area in financial engineering. Except the require classes are set in first two classes, you can also choose the class you like in third semester. After enrolled in this program, I certainly have improvement on my academic path!

I am an alumni graduated at December 2018, and after 2 months then I landed a job in Chicago. The general employment rate is good for our class. Most of our classmates received offers from January to March. Quite a lot concentrated in quantitative finance related positions, others include like sales and trade, data science and analytic roles etc. U of I is quite competitive in great chicago area, where many big-name finance companies located at. In recent years, we witnessed some continuous progress and changes in this MSFE program, e.g. some courses are more focusing on industry related topics, other than just theory and formula based courses. Honestly, there are still long way to go for this program to be a top level one. But my recommendation is, if you can get admission or offer from a MFE program in CMU, MIT and Princeton or other programs at this level, definitely go to these programs. If you choose U of I, don't get frustrated, you still have a great chance to land a good job!

I graduated in 2015 and currently work in Chicago. Here's my two cents on the program:
Strength:
- Well rounded curriculum
Having graduated and met with other people of similar programs, I feel our program offers a very well-balanced academic curriculum: a bit of statistics, a bit of programming, and a bit of finance, all in the first semester. I've read reviews where people think the finance courses are useless, but in my experience, those courses gave me good small talk material during interviews to show my interest in the field.
- U of I has strong pull on employers
This is different from our program's career services, more on that later. Most people come to a Masters program with one thing in mind: a better job. In this sense, U of I has plenty of resources available for that: in my day, there were 3 career fairs a semester, with more than 200 companies coming to each of them. Having been on the hiring side going to other schools in my recent years, I can tell you UofI's pull is as strong as any of them.
Weakness:
-Career Services
So it was surprising to me when the students are not exactly taking advantage of the career opportunities provided. I think it could have been a combination of the student demographic and negligence of the program on career counselling; but when school started I was one of the few people that went to career fairs in September. Given that most companies finish intern hiring in the fall nowadays, when spring comes many of my peers were scrambling to find an internship.
-Location
Situated in Champagne makes it difficult network with alum and professionals. The programs does try to remedy this with a colloquium set in Chicago, but I don't think it's enough. With that being said, the curriculum did give you enough time to network on your own though: I flew myself to New York to meet with people, and met up with alum in Chicago for coffee chats when I could. Like all things in life, you just have to make the right trade offs: getting important industry knowledge outweighed missing one assignment mark.

Final thoughts:
For the initiated student, UofI has a lot of opportunities to offer; but none of them will be spoon-fed to you. I think the program can strengthen itself in terms of alumni connections, and educating students on the job market during orientation. I don't think having a lot of international students is a problem (I was one), but their expectations needs to be adjusted.

I can't believe there's a review calling this program a fraud. Hey, I don't know what universe you are from, but in this one, it's a fabulous Master's program, where you can learn much more than what's enough to get you a decent job in quantitative finance. And Dr. Lane is always doing his best to make great use of our tuition, providing networking opportunities, elective classes and even hotel accommodations in Chicago.

Sorry if I got a bit too emotional here, but my point is, MSFE at UIUC is a great program where you have a well selected list of courses covering a wide range of knowledge in quantitative finance, such as statistics, derivatives, risk management, etc. The academic training is also paired with professional projects from industry partners. Most professors are extremely good at teaching and even world-famous. To be honest, I did encounter one professor not so dedicated in the course, but the problem got well-addressed by the program. In that case, giving HONEST and FAIR feedback is important, and naturally it takes time for the program to address the problem, and that doesn't mean the director does't take it seriously.

Also it's not true that we only have 1 elective. in the third semester you choose all your 4 courses from a list of finance and engineering courses...including courses from UIUC's well-respected CS department.
A bit more flexibility in the first 2 semesters sounds good, but honestly in the first 2 semesters, the required courses are all fundamental ones in quantitative finance, and you really need to take them if you want to understand what your colleagues are talking about later in the work place.

Overall, great program with dedicated crew, decent professors, and a lot to offer for the tuition. It's also a great place to make some lifelong friends.

As a current MSFE student, I really like this program. Class size is relatively small. The curriculum is very well structured. The program is very intense. Dr. Lane and other staff members are doing their best to provide us networking opportunities.

Intensive coursework, excellent professors, can learn everything needed. There are cutting edge stuffs including most advanced derivative valuation models, most prevailing numerical methods, machine learning technics and so on while very fundamental yet profound knowledges in programing, finance, math, stat and economics are also provided.

As a current student, I am finding this program extremely well structured. There is a specific focus and attention given to the program in terms of what is taught and how the curriculum can be directly linked to the current financial world.
The program gives access to both engineering and business career fairs with a widest range of options in positions and companies to choose from.
Morton Lane is the director and is pro actively involved in creating networking opportunities for students. The practitioner series is one step in that direction.
The program is rigorous, tough and demanding but I definitely see excellent prospects for students.

Excellent experience.
The practicum choice in the second semester gives MSFE students a valuable opportunity to cooperate with companies and gain real world experience in financial engineering industry. It is really helpful for MSFE students to find an internship or a full time job in US. A lot of students of class 2014 have found internships in US this summer.

I graduated from the program in 2011. Since after then, I have met people from other comparable programs through work or social networking.

I would like the comment that this program really hits the sweet spot in terms of elegantly balancing course work between academic rigorousness and industrial practicality by connecting world class engineering school resource with strong (and evolving) exposure to financial industry experience in Chicago as well as elsewhere. I am very glad to have made such a decision to go to UIUC MSFE.

About the program:
Overall, my experience at UIUC was positive. The program was demanding, and although I joined some social organizations like the tennis club in my first semester, I was unable to find time later on to do anything aside from studying and looking for jobs. I learned a lot and gained a lot from attending the program. My technical/quantitative skills have vastly improved.

-The people at the MSFE office are very nice and accommodating, and I sense that they are truly committed to providing for their students and helping them succeed.

-The professors (for the most part) are very respectful of the students, and committed in helping them succeed.

-The student body, in my year, was too homogenous in culture. I think the program should strive to achieve a balance in class diversity – as they seem to have done for the 2015 class.

-The practicum is really what makes this program unique and exceptional. There is really no replacement for hands-on experience with an employer. You can think of the practicum as an apprenticeship. There was a lot of diffusion of knowledge between the sponsor and our team, and our sponsor was also nice enough to offer compensated summer work for students whom were unable to find summer internships. The practicum for us was where we really saw the interdisciplinary blend of practices come together in finance, as we saw how text-mining was used in finance for Twitter sentiment scoring, got to work with the data and build forecasting models, and also receive feedback on our work throughout the entire process. Skills obtained through the practicum could not be obtained through the classroom.
However, the biweekly meetings in Chicago was a bit strenuous for me particularly, because I also chose to take extra courses that were in session on Fridays. Going to Chicago takes about 3-4 hours one way by Greyhound, and we had to allocate every other Friday for the trip to go to Chicago for a 1-hour meeting with the sponsor. In the end, I was overloaded with work throughout the semester, and I wish I had the capacity to put in more time and effort for the project.

-There were too many mandatory meetings in the second semester in Chicago like the IAQF panel and the volatility workshop. I think mandatory meetings in Chicago should occur on Saturdays, so students taking classes on Fridays don't have to skip class.

-Career services/preparation really needs to ramp up.

About the University of Illinois:
Apart from the program, my experience at UIUC was very positive. I took 5 classes outside of the MSFE program (machine learning, finite element methods, partial diff. eqs, econometrics, and mathematical statistics), and they were all demanding, but truly world-class. This amount of coursework, combined with the rigorous contents, was a bit too much for me and affected my GPA, but I think the exposure I got was really worth it. It was an eye-opening experience where I got to take the same classes with statistics phds, economics phds, computer science phds, and mathematics phd students, and see for myself how I would do comparatively. The University of Illinois is truly a top university across all these fields and more. Financial engineering is by definition an interdisciplinary field, and I think it is important for any top institution to stay true to this interdisciplinary spirit, and offer elective coursework in all these areas. Given that the need for quant professionals changes constantly in the finance industry, I believe that a program that prescribes a fixed curriculum risks losing relevance to industry quickly. In this regard, the University of Illinois exceeded my expectations with the vast amount of top-notch coursework available. As a direct result of this, I was able to obtain interviews across a wide range of positions from algorithmic trader, to risk management consultant, to data scientist positions.

Apart from my review, I have a couple suggestions (ideas) on how the program can be improved:
1. Career Services (for Chinese Students)
- Make a separate career services specializing on getting Chinese students hired, and diffusing the sino-american cultural barriers. I think many of the Chinese students are technically talented enough to pass the technical interviews, but I would guess they must get held up in the behavioral interviews.
- I think that career services should already begin when the student enters the program, where students should identify a target position they want to apply to and receive counsel on how to strategize and build their resumes for those positions.
- Emily's occasional e-mails notifying us about open positions and events/tips weren't very helpful. I think quant interview workshops and role-playing workshops is what is really needed. Maybe bring in an outside quant interview expert for a day to hold a workshop or something(?).
- I would like to see some sign that the department is actively soliciting employers to come to campus and recruit MSFE students. At the present, the only visible relationship between the department and employers is the practicum, which I am hoping would change.
- Things they could use help on include building their resumes for specific positions through experiences and coursework, behavioral and technical interviews, finding the right jobs to apply to, how to approach recruiters at career fairs, understanding the typical recruitment process at American companies, understanding the power of acquainting with the recruiter beforehand, how to write follow-up e-mails, strategies on getting past the 'do you have work authorization' question, etc.
- Chinese students also need to recognize that they need to accept some American values and 'americanize' if they want to find jobs in U.S.

2. Re-evaluate the current curriculum
- While I realize that derivatives valuation is at the heart of the financial engineering discipline, the reality appears to reflect that the need for such people in industry is fast declining. Many of the tools acquired through an FE education are still relevant – like risk management, optimization, clustering, monte-carlo simulations, time-series modeling, and programming. However, it appears that current industry is more interested in using these tools within the context of data analytics. I am unsure of how relevant courses like financial economics and stochastic calculus are in the current industry, and they could be replaced to teach more data-oriented skills like Hadoop, cloud computing services like AWS, SQL, machine learning & data mining, data visualization, and statistical programming, that could make students more employable.

3. Standardize the programming language used throughout the curriculum, and then implement a baseline standard for programming skill across all students
- The employability of a student is highly correlated with that student’s programming skills. For a student to gain a high level of competency in a language, he/she needs to continue using it for a period of time. To make this process faster, I really believe that the program should just stick to one language used throughout the entire curriculum, and I further argue that the ideal language for this would be Python.
- With the current way things are, a lot of students graduate with little to mediocre programming skills, and most students graduate with Matlab being their primary language of choice. I believe this model is unsustainable because Matlab is rarely used in industry, and it is a superficially easy language to use. Programming skill in Matlab does not carry over to many other languages.
- Many students enter the program with no prior experience using Matlab, and then get introduced to C++ and R - all while still climbing the learning curve for Matlab. This results in them never fully climbing the learning curve for C++ or R or Python. Instead of trying to learn all these different languages at once, it's better to just concentrate on learning one main language that can be used in almost all situations, which isn't Matlab.
- Financial computing teaches us the type-safe language C++, which is useful to know, but a different beast from dynamic languages like Matlab, Python, and R. For the purposes of finding quant employment outside of quant development, knowledge of dynamic languages is more important, and Python seems to be the king in this field. Python seems to suite all the needs of a financial engineer in one language, and it is used widely in industry as opposed to Matlab.
- Python is probably the most frequently used language in the growing area of data analytics.
- I think that programming is important enough that the MSFE department should monitor and set a baseline standard for how well the students can do it.

We had worked with six students from the MSFE program at UIUC on a quant project for around 5 months this year. These students have very strong quantitative skills and are good at solving practical problems. You can also find star developers who can really code in C++ among them. All the students in this group worked very hard and were easy to work with. I highly recomend this program.

I work for the University of Illinois's Investment Department, and we partnered with the Financial Engineering Program as part of their practicum program. The students did an excellent job creating a scenario analysis database for us. Dr. Lane was very involved in our project and provided great insight. We were impressed not only with the final product, but also with the quality of students and their experience through the program.

As a potential employer of MSFE students, I feel the program offers a well-balanced and practical curriculum supporting a deeply analytic approach to the financial markets. My experience with the students participating on my practicum has been very thoughtful and quite useful.

I just graduated from this program (Dec 2014). It is a great program because it concerns a lot about technical skills. You can learn a lot in statistics, programming. Of course, courses like Risk Management and Financial Derivatives make me equipped with detailed knowledge and skills applied in finance industry. You could expect a lot after you finish your study. That is why I found a job in Chicago.

I learned a lot in this program, and the students here is outstanding! What's more the director and professors here are very brilliant and willing to help students with their learning and job hunting. Students feel comfortable to study, live and discuss with each other!

It is one of the program that emphasizes much on programming which I have ever known. Its practicum also gives students a good chance to devote themselves into real problems and social with industry elites.

The MSFE program has a one of a kind curriculum that allows you to study a wide variety of subjects in all relevant fields that define quantitative finance.

My favorite courses were Risk Management, Financial Derivatives and Market Microstructure, since they provide the ideal foundation for algo trading.

The Practicum project in the third semester gives you immense exposure to the industry and practices - and the best part is that you get to apply what you've learned to very realistic, implementable and professional projects.

I'd recommend this program to everyone who's interested in pursuing a career as a quant.

While I cannot in a timely fashion explain all of the reasons as to why this program is exceptional, I can at least express my gratitude for the endless opportunities UIUC MSFE has provided me. Albeit rigorous, exhausting, and daunting at times, this program is ideal for candidates interested in:

studying stochastic calculus in a financial context; using statistical techniques for time-series data; building valuation methodologies; leveraging a handful of programming languages; employing optimization techniques; investigating numeric methods; networking with financial institutions; contributing to confidential practicums; joining a community of accomplished alumni.

This program's flexibility has also enabled me to study data structures, numeric algorithms, and random processes at a more advanced level, in particular the applications of artificial intelligence and machine learning, parallel numeric algorithms, and human-computer interaction.

Following graduation, a considerable number are tempted to pursue doctoral degrees. While this is not surprising, I think the vast majority are as anxious as myself in merging a professional career with this newly instilled skill set that has such broad applications.