Mathematics with Statistics for Finance

Mathematics with Statistics for Finance brings together two disciplines that have become indispensable to modern financial markets and institutions. Pure and applied mathematics provide the rigorous analytical foundations on which quantitative finance is built, while statistics provides the tools for modelling uncertainty, analysing data, and testing hypotheses about how markets behave. In an era when trading, risk management, pricing, and regulation all depend on sophisticated mathematical and statistical reasoning, graduates who can work fluently in both areas are exceptionally well placed.

At Imperial College London, this three-year, full-time degree is taught to the standards of rigour and depth that Imperial is known for. You will engage with concepts that develop directly from A-level mathematics while also encountering new ways of thinking that are distinctive to university-level work. The mathematical content covers analysis, linear algebra, probability theory, and differential equations, among other areas, while the statistics component addresses inference, regression, time series analysis, and stochastic processes.

The finance-oriented statistics strand connects these mathematical tools directly to the kinds of problems that arise in financial markets, including option pricing, portfolio optimisation, and risk modelling.

Graduates from this programme are strongly positioned for careers in quantitative finance, where roles in trading, structured products, risk management, and financial technology increasingly require the mathematical and statistical literacy this degree develops. Investment banks, hedge funds, insurance companies, consultancies, and regulatory bodies all recruit graduates with this profile. The analytical skills are equally valued in data science, technology, and research roles across many sectors.

Many graduates also go on to postgraduate study in financial mathematics, statistics, econometrics, or related fields, deepening their expertise for specialist or research careers.