MSc Financial Mathematics (MSc FM)
Mathematical and statistical modelling of financial markets with compulsory C++ and Python machine-learning modules. In semester B students pick one of three streams: investment management, banking and risk, or quantitative pricing/development/research.
What you’ll study
Core
- Financial Instruments and Markets
- Foundations of Mathematical Modelling in Finance
- Machine Learning with Python
- Programming in C++ for Finance
- Project Dissertation
Electives
- Advanced Computing in Finance
- Advanced Derivatives Pricing and Risk Management
- Advanced Machine Learning
- Bayesian Statistics
- Bond Market Strategies
- Computational Statistics with R
- Credit Ratings
- Digital and Real Asset Analytics
- Financial Data Analytics
- Forecasting with AI
- Neural Networks and Deep Learning
- Private Equity and Venture Capital
- Risk Management for Banking
- Systemic Trading Strategies
Source: qmul.ac.uk ↗
Before you apply
- Background
- UK 2:2 (55%+) in Mathematics or a subject with a strong maths component (e.g. Physics, Engineering, Computer Science); 2:2 (50%+) considered with relevant work experience
Source: qmul.ac.uk ↗
After graduation
- Typical first roles
- Quant Developer, Quantitative Analyst, Quantitative Investment Strategist, Market Risk Associate, Data Analyst
- Employers
- EY, PwC, Macquarie Group, Spreadex, London Royal Asset Management, Schonfield
Source: qmul.ac.uk ↗
Want to see what employers ask for? Browse open quant roles.
What students and graduates say
Threads from QuantNet and other forums where applicants, students and graduates discuss this programme. They’re personal views and may be out of date.
- Best Quant programs in UK (QuantNet)
- what UK quant MSc should i apply to? (QuantNet)
- Quantitative finance masters comparison UK (QuantNet)
- Birmingham or Queen Mary (QuantNet)
English-language requirement text was truncated in fetch.
Checked 6 November 2026 against the sources linked on this page. Fees, units and requirements change each year, so confirm them on the programme’s website before applying.