This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.
Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.
As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.
The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as machine learning and big data processing.
The programme is offered:
The Bank of England regularly visits QMUL as part of our MSc Industry talks
Citi sponsor Maths careers events on campus
This MSc programme is directed by Dr Michael Phillips, Senior Lecturer in Financial Mathematics. Prior to joining Queen Mary in 2012, Michael worked for over 10 years as a quantitative analyst and software engineer for a number of well-known investment banks in the City of London. There he developed state-of-the-art pricing models for a wide range of financial products, including interest rate derivatives, commodity options and exotic credit derivatives. He has also spent time working on a bond trading desk, devising trading strategies using proprietary statistical arbitrage techniques. Michael is a graduate of Cambridge University, and holds a PhD from Brunel University (London) in Mathematical Physics.