Imperial College London - MSc Mathematics and Finance

My initial impression of the course was that there would be a good balance between maths and finance, and I was particularly looking forward to meeting people in industry and getting a good placement. In fact, what I enjoyed most about the course was the strong link with industry.

The weekly presentations by banks, asset managers and fintechs, as well as the lectures by practitioners, were extremely useful. They were very practical and I learned a lot from speaking to the presenters, both about the nature of a job in quantitative finance as well as opportunities to apply to their internships and off-cycles.

But what struck me about the course material was the lack of focus on finance. Since I have more of a stats, financial maths and programming (actuarial) background from my undergrad, rather than pure maths, I was unable to apply what I already knew and didn't encounter a lot of what was assumed. This lead to me struggling with more rigorous and abstract topics, such as measure theory and stochastic calculus. Even seemingly practical topics like statistics and simulation methods were dealt with in an unusually theoretical way, though coding was still involved to a small extent.

As a result, I felt that what we were learning did not feel very compelling at times. In fact, there was not one module available which discussed any finance theory topic (e.g. economics, financial markets, accounting, financial management) in particular detail, which was a little disappointing. I understand that the course is taught by the Department of Mathematics, but to have not even an introductory all-in-one module is strange, especially given the course title.

Lastly, the course evidently has an excellent reputation among employers. We often received job descriptions from them by email, relating to either internships or their available projects for our MSc thesis. In fact, this was how I applied for and got my thesis internship, which I then converted into a full time role. Those who don't do their thesis with a company instead do it internally with an academic supervisor. But even so, you would still be well-positioned for applying to jobs after the master's.

On balance, I think the course has been very enjoyable. Being in London, Imperial is in a great city and I'd highly recommend making the most of it. For people who enjoy lots of pure maths, that's exactly the experience you'll get, with a little bit of finance and programming colour to it (Python and C++). But I believe the most important thing to get out of it is a foot in the door in a big bank, or the opportunity to find out if a smaller fintech might be better for you!

In summary, it's a highly rigorous mathematical finance course, with great prospects for a job in the industry.

The MSc is a good programme if you’re looking for a study to break into quant research. There are more than enough courses which give a good overview of the state of the art research currently being used in the industry. As with all programmes, in general teaching is of a good level, with some positive and negative outliers. However, overall, I would say the MSc is a good programme, especially if you are looking for a solid Mathematical foundation to break into the industry. With that, the good reputation of Imperial also helps, as in general, the programme is well-known to be of a good level by practitioners.

Overall, I think the course is great; it covers all the important topics of quant finance and is mathematically rigorous, making it great preparation for a job as a quant at a top bank, hedge fund etc. The optional modules allow you to explore a wide range of interesting topics, such as quantum computing or deep learning. All the lecturers are highly successful academics in their field. The department has great connections to the industry and there are regular talks by companies discussing the work they do and advertising quant roles they have available.

I can't say I have enjoyed it massively because of how incredibly intense it is. You have to keep up with lectures and content and completing coursework alongside preparing and applying for quant internship positions. I think even some of the most academically gifted students would find this course a challenge because of the amount of work.

The two standout aspects of this program are the career services and the electives available. A lot of the reviews here have already touched upon it but the career services in the program are excellent. With weekly career fairs and interview preperation sessions the program ensures its students are well equiped to enter the workforce. In my opinion the electives were first class, in particular the Market Microstructure and Topics in Quantitative Finance ones. Through them one can get a very good idea of what the current research landscape looks like. These two aspects of the program complement each other well, balancing both theoretical and practical knowledge.

This is an experience of great value with courses covering various topics that could be useful whether students choose to do a PhD or pursue a career in the industry. Course materials are so well prepared that I still go back to them occasionally after graduation; the quality of course delivering however may vary, which is understandable as the programme is trying to cover a wide range of topics in a short period of time. Career service is a highlight as there are weekly workshops with institutions, where opportunities are advertised and students get a chance to speak to practitioners and understand what is happening at the frontier. Many of the alumni could turn out to be future colleagues of a cohort.

- A combination of math, computing, and finance.
- In terms of career services, it is second to none.
- Weekly career talks/ events, enabling you to make connections.
- A wide range of options for elective modules.

Advantages: Very good links with the financial industry that allows you to secure an internship.
Disadvantages: It is only a one year programme, so there are many deadlines and it becomes quite stressful. Also, the teaching quality of the lecturers could be improved considerably.

I am writing this review at the request of Andy Nguyen :)

Though I should first mention that my review of this program falls under a bit of an "outlier" review.

First of all, before joining this program I was already an undergraduate at imperial, studying mathematics, and I got into the program through a recommendation letter from Jack (the course director).

Secondly, I entered the program already with QR internship experience at a top hedge fund, and landed a QR position at a tier 1 hedge fund about a month into the program. Ever since then I have not been interacting with the program much if I'm going to be honest.

With regards to my experience with Jack, he was my undergrad thesis supervisor and is currently my personal tutor for this MSc program so he is very approachable and friendly.

With regards to the lectures, the lectures are nice I guess- they are all recorded so you can view them again at your own leisure. Furthermore, there are office hours where you can go and visit the lecturers to ask them further questions.

Finally, and possibly most importantly, lets talk about things pertaining to careers/placements on this program. Every week there is a practitioner series (where people from certain companies come in and talk about the work they're doing, some examples include Citadel, JPM, Nomura etc), there is also a careers fair (where a company comes in and present their opportunities for an hour followed by networking), and also interview preparation sessions which are taught by some professors. Also, there are lots of opportunities that are offered specifically for people on this course that are advertised by Jack (Kaiju Capital Management, BNY Mellon, etc).

PS: So far we seem to be doing better than Oxford MCF in terms of placement/job offers (as in, a higher percentage of our cohort have offers so far).

The highlight of the math and finance program is its excellent career service. The program has direct industrial connections and a strong alumni network. Career lectures and interview tutoring sessions are held every week. Exclusive interview opportunities are provided by some banks and funds.

The program has very relevant coursework. Strong focus on mathematical finance but also enough coverage on machine learning and coding practice.

Most graduates will join various quant teams at investment banks or hedge funds in London and a few will go for a PhD.