MSc Financial Mathematics

At Queen Mary University of London, the MSc Financial Mathematics is designed to give you practical, industry‑relevant skills as well as deep theoretical understanding. You won’t just learn formulas you’ll use real financial tools, professional‑grade programming languages, and industry data, working step‑by‑step through hands‑on modules, programming labs and a substantial independent research project. You’ll also have access to dedicated facilities that support collaborative study, advanced computation and financial technology applications, giving you the experience employers are looking for in quantitative finance, risk management and data‑driven roles. 

Your experiential learning includes:

• Dedicated computing labs with Bloomberg terminals — practical classes and assignments are delivered in specialist computing environments where you work directly with industry‑standard financial data platforms and software tools, just like you would in a financial institution’s analytics team. 

• Hands‑on programming in Python and C++ — modules such as Machine Learning with Python and Programming in C++ for Finance emphasise practical coding skills, giving you experience with key languages used in quantitative analysis, algorithmic trading and model development.

• Machine learning and data analytics applications — you’ll implement real data tasks using Python to build and test models that extract insights from financial markets, covering regression, classification, neural networks and more. 

• Real quantitative modelling and financial systems practice — coursework in modules like Foundations of Mathematical Modelling in Finance and Advanced Derivatives Pricing and Risk Management has a strong computational component, giving you experience applying math and statistics to pricing, risk and market behaviours.Substantial independent Project Dissertation an entire semester and summer are dedicated to your 60‑credit research project, where you explore topics such as exotic option pricing, portfolio optimisation or numerical methods — often involving real data, programming, and advanced computation. Choice of specialism streams — the programme lets you focus on areas like Investment Management and Data Analytics, Investment Banking and Risk Management, or Quantitative Pricing, Development and Research, tailoring your practical skill development to your career goals.

• Collaborative learning and tutorials — your education combines lectures with regular tutorials and independent study, building teamwork and problem‑solving skills that are essential in professional and research environments. 

• Modern campus and study spaces — you’ll learn in QMUL’s recently upgraded Mathematical Sciences building, with high‑quality teaching rooms, private and group study areas and access to extensive library resources including thousands of mathematical books and journals. 

• Academic Adviser support — every student is assigned an Academic Adviser who provides guidance throughout your studies, helping you navigate coursework, project choices and career planning. 

Graduates of MSc Financial Mathematics at QMUL enter quantitative and analytical careers where advanced mathematical and computational skills are in high demand — particularly in finance, risk and data domains. Across the School of Mathematical Sciences’ postgraduate cohort, around 90 % of graduates are in employment or further study within 15 months, with strong representation in highly skilled roles and average salaries well above the university average. 

Typical graduate roles include:
• Quantitative Analyst / Risk Analyst
• Data Analyst or Financial Modeller
• Investment or Market Risk Associate
• Quantitative Developer / Pricing Specialist

Future Progression & Opportunities:

• University services that help students to employ: QMUL’s dedicated Career Development Service and in‑school support offer personalised guidance with CVs, interview prep, employer networking, internship and job opportunities — tailored especially for STEM and finance‑oriented students. You’ll also have access to industry contacts through seminars, employer events and connections with City professionals. 

• Employment stats and salary figures: Data aggregated across MSc programmes in the School of Economics and Finance shows 90 % of graduates in work or further study and an average UK salary of around £34,000 15 months post‑graduation. Additionally, QMUL postgraduate maths graduates report an average salary of £53,000, which is notably higher than the university average — highlighting strong long‑term earning potential. 

• University–industry engagement: The programme is taught by academic staff with experience in investment banking and financial markets, and features practical elements such as machine‑learning in Python, C++ programming, and the Queen Mary University Student Investment Fund (QUMMIF), helping you build real‑world skills and network with professionals. 

• Long‑term accreditation value: Although the programme itself isn’t separately accredited, it sits within QMUL’s School of Mathematical Sciences — a research‑led department with strong reputation and global recognition that signals advanced analytical capability to employers across sectors.

• Graduation outcomes: Students from this MSc have progressed into roles such as Quantitative Analyst, Data Analyst, Market Risk Associate, IT Audit Analyst and Quant Developer with employers including EY, PwC, Macquarie Group, London Royal Asset Management and Spreadex, showing diverse career entry points and strong industry relevance. 

Further Academic Progression:
After finishing the MSc, you could advance to research degrees (MPhil/PhD) in Financial Mathematics, Quantitative Finance or Applied Mathematics if you’re interested in deep technical or academic work. Some graduates also choose specialised professional certifications (e.g., in risk management, financial engineering, actuarial science or data science) to further enhance employability and career trajectory in quantitative finance or analytics fields.