MSc in Mathematical and Computational Finance - Alumni profiles

Ambroise Desplechin

Quantitative Analyst at Nomura International

MSc MCF 2009

"When I joined the MSc MCF at Oxford, I had already worked two years as a Quant. This MSc was an unique opportunity to strengthen and broaden my knowledge in mathematical finance.

This programme provides a strong background in all the core areas of mathematical finance, taught by leading researchers in the field, and gives the chance to attend regular seminar series with distinguished speakers from both academia and industry.

Claire Qin

FX Desk Quant at Morgan Stanley

MSc MCF 2010

"The Oxford brand gives people a sense of trust that you can take on whatever is put in front of you. The program's rigorous approach to mathematical finance problems not only helped me get through bank interviews but also make my day-to-day job much easier."

Sylvestre Burgos

Quant Analyst at JP Morgan, formerly DPhil student at the University of Oxford

MSc MCF 2009

"I graduated from the MScMCF class of 2009. The courses were well structured with extensive homework and gave me essential technical skills that helped me secure an offer for a quant associate summer internship at Barclays Capital.

Attending the many practitioner lectures and meeting the faculty (not to mention Oxford's setting and its dynamic social life) were inspirational and convinced me to further my knowledge of financial mathematics and to continue my studies with a DPhil within Oxford's Mathematical Institute and the Oxford-Man Institute of Quantitative Finance.

On a personal level, I've also loved the atmosphere and made very good friends I am still in touch with."

Jason Zhao

Quant trader at Barclays Capital, formerly at J.P. Morgan and Goldman Sachs

MSc MCF 2010

"The MSCMCF is successful in terms of both depth and width: all components of the course are very demanding -- they dig deep enough to let you digest the concepts and techniques thoroughly; there are various optional components to choose from, and that gives you the flexibility upon graduation to take up either a classic role as a derivative quant/trader or other roles like an algorithmic trading quant, which is what I finally turned into.

The course is theoretical enough to be an ideal preparation for a PhD programme in quantitative finance; it is also very practical, which is reflected by the top practitioners that the course invite to give lecturers -- many of them are globally well-known figures in industry. There is also an intensive C++ module that prepares you to code professionally."

Juraj Spilda

PhD Student

MSc MCF 2010

"In many ways, the curriculum of the MScMCF takes you to the cutting edge of modern financial research. When writing your dissertation, you will be working on small pieces of original research under the supervision of world-leading experts. The exposure to the open issues in the field motivated me to pursue further independent study and research as a PhD student.

The program is intense and you are going to spend many late nights sitting over coursework. However, the unique support environment of Oxford colleges, the wide network of university societies and a constant stream of engaging events within the University will ensure that you can always make the best of the little free time you have."

"This MSc definitely made a significant contribution to me geting a job quickly after graduation despite a tough environment."


Cheng Zhu

PhD student at McGill University, formerly Quantitative Credit Risk Analyst at EDF Trading

MSc MCF 2011

"The MSc MCF is perfectly structured in three main aspects: mathematical essentials; financial markets; and numerical methods.

The materials and topics covered in lectures, seminars and mini projects consolidate my technical abilities and bridge the gap between industries and academia, letting me adjust well to a challenging investment banking role.

I am also very grateful to the responsive and dedicated professors, lecturers and faculty members. I got a lot of support and advice from our course staff. This unforgettable experience aroused my research interest and also allowed me to develop relevant skills."


Zhenru Wang

DPhil student at The Mathematical Institute, Oxford University

MSc MCF 2015

"This MScMCF helped me build not only skills in maths finance for going to the industry, but also provide me with a solid foundation to further continue my DPhil studies. The materials are well adjusted to the current trend in the quant world, and the courses are well balanced between theory and practice. The dissertation project in the Trinity term gave me such an excellent opportunity to work with my supervisor. I enjoyed it very much, and thus I continued my studies."


Oliver Sheridan-Methven

Oliver Sheridan-Methven

- MSc student at Imperial College London, 

- Formerly Quantitative Developer at Citadel Securities

- Formerly DPhil Student at the University of Oxford’s Mathematical Institute (InFoMM CDT).

MSc MCF 2016

Oliver pic

"I graduated from the MSc in 2016, previously having done a masters in physics. I was unsure if I wanted to pursue a career or a PhD, and the MSc was ideal for preparing me for either. The syllabus was strong on both the theory and practical side, requiring large amounts of programming. The research projects at the end were a great opportunity to focus on the more interesting topics.

During the MSc I interned at Man AHL working in fixed income and data innovations, for which the MSc provided a good base of knowledge both in theory and practical skills. 

Since the MSc I completed a DPhil at Oxford in applied mathematics focusing on stochastic simulation techniques, and was involved in teaching subsequent MSc MCF cohorts. After completing the DPhil, I worked at Citadel Securities as a quantitative developer in their advanced scientific computing team. Currently I am undertaking an MSc in Advanced Computing at Imperial College London.  

The main strengths of the course are the introduction to stochastic calculus, applications in derivative pricing and LIBOR models, and teaching C++ programming skills and effective programming practices."


Saad Labyad

DPhil student at The Mathematical Institute, University of Oxford

MSc MCF 2018

"I graduated from the MSc MCF class in 2018, with a double degree from an Engineering school in France. I embarked upon this master’s course, aiming to understand the fundamentals in Mathematical Finance. I wanted to master stochastic models and numerical methods before applying for PhD programs at Oxford and in the US. The course assisted me in achieving my goals. It couldn't have happened without the experienced professors who taught me. They undoubtably form a top level research group, and their diverse work interests allowed me to gain different perspectives and advice. Outside the taught element to the course, the mathematics, statistics and computer science departments provide a number of fascinating seminars and workshops on a range of subjects, and the department facilities are second to none. I believe that this is an environment build to learn in, whether your objective is to pursue a career in academia, or whether you want to work in quantitative research in banks or hedge funds, you will be sure to reach it".

Olivia Pricilia

Alumni picture





DPhil student at Mathematical Institute, University of Oxford

The MSc in Mathematical and Computational Finance has helped me to develop essential mathematical finance and programming skill required for both industry jobs and academic research in quantitive finance. The course is well-structured and strong on both theoretical and practical sides. The MSc dissertation in the last term (which can also be done in conjunction with an industry internship) provided students with a great opportunity to dive deeper into an interesting topic in mathematical finance under guidance from one of the faculty members, while gaining research and/or industry experience.

After completing the MSc program in 2021, I worked at Goldman Sachs and JP Morgan, before returning to do DPhil in Mathematical Finance (CDT in Mathematics of Random System).

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