MSci Hons Financial Mathematics with a Professional Placement

5 Years On Campus Bachelors Program

Queen Mary University of London

Program Overview

The MSci (Hons) in Financial Mathematics with Professional Placement is a five-year programme that combines advanced mathematics, finance, and statistics with real-world industry experience. It is tailored for students aiming to develop deep quantitative and analytical skills, while gaining practical exposure in finance, risk management, or actuarial roles.

Curriculum structure:

Year 1
The first year builds a strong foundation in mathematics, statistics, and introductory finance. Students study Applied Calculus, Applied Probability & Statistics, Numbers, Sets and Functions, Introduction to Probability, and Computing and Data Analysis with Excel, equipping them with essential analytical, statistical, and computational skills.

Year 2
The second year develops advanced mathematical and statistical knowledge, while introducing specialized finance concepts. Core modules include Statistical Modelling I, advanced probability and statistics, and elective modules such as Actuarial Mathematics I, Complex Variables, Introduction to Algebra, or programming/data-analysis electives, allowing students to begin focusing on finance or actuarial science.

Year 3
The third year continues advanced study in mathematical and financial theory. Students study topics such as Financial Mathematics I, Stochastic Processes, and Random Processes, alongside electives in derivative pricing, numerical methods, and computational finance. This year further strengthens quantitative and analytical skills in preparation for the placement.

Year 4 (Professional Placement Year)
The fourth year is a paid professional placement in the finance, insurance, or actuarial sectors. Students gain practical experience applying mathematical and statistical techniques in real-world contexts, building industry knowledge, professional skills, and networks that enhance career prospects.

Year 5 (Final Academic Year)
In the final year, students return to complete advanced modules and a substantial independent project integrating mathematics, finance, and computational methods. Core and elective modules may include Financial Mathematics II, Advanced Stochastic Modelling, Numerical Methods in Finance, Machine Learning for Finance, and the MSci Project. This year allows students to specialize in areas aligned with quantitative finance, risk analysis, actuarial science, or data-driven financial applications.

Focus areas:
Quantitative mathematics, probability and statistics, stochastic processes, mathematical finance, statistical modelling, computational finance and data analysis, professional finance experience, risk modelling, actuarial mathematics.

Learning outcomes:
Graduates develop advanced analytical and quantitative skills, deep understanding of mathematical finance, proficiency in statistical modelling and computational methods, and practical industry experience. They are prepared for professional roles in banking, risk management, finance, insurance, and quantitative analysis.

Professional alignment (accreditation):
The programme is delivered by the School of Mathematical Sciences and aligns with industry standards for quantitative finance and actuarial work. The professional placement ensures students graduate with practical experience valued by employers.

Reputation (employability & career prospects):
Graduates are highly sought after by global financial institutions, consulting firms, insurance and actuarial companies, and other quantitative-driven industries. The combination of advanced mathematics, finance knowledge, and placement experience ensures strong career readiness in high-demand sectors.

Experiential Learning (Research, Projects, Internships etc.)

The MSci in Financial Mathematics with Professional Placement combines advanced mathematics, financial theory, and real-world experience — preparing students to become highly competent and career-ready in finance, quantitative analysis, and risk modelling.

Experiential Learning & Practical Exposure

Students benefit from a blend of mathematical coursework, computational training, financial-modelling skills, and industry exposure via a placement year:

Emphasis on mathematical finance and numerical methods: students build and analyse financial models, apply stochastic methods, run numerical simulations, and solve real-world financial maths problems.
Integrated computing and programming skills for writing code to solve applied problems, model financial markets, and work with finance-related data.
Full professional placement year in industry, gaining hands-on experience in roles such as data/quant-analysis, banking, risk, investment, or financial modelling.
Placement support from the School of Mathematical Sciences, including guidance on applications, interviews, and mentorship.
Final-year research project in financial mathematics, allowing students to combine theory, computation, and industry insight.

Programme Content & What Students Learn

Solid foundation in pure and applied mathematics, essential for financial modelling.
Techniques for financial modelling and numerical methods, applied to banking, fund management, insurance, risk analysis, and related sectors.
Computational and programming skills to produce quantitative, data-driven solutions and engage in financial computation.
Final-year research project in financial mathematics to explore advanced topics and prepare for quantitative finance or academic/research careers.

Why This Degree Gives a Competitive Edge

Combines analytical mathematical depth with practical finance-industry experience, making graduates stand out in banking, investment, fund management, risk, insurance, and quantitative finance.
Programming and computational skills ensure graduates are ready to handle data, numerical problems, and real-world financial tasks from day one.
Professional placement provides workplace-ready skills and strengthens employability.
Final-year research project bridges theory, computation, and finance, giving an advantage for high-level quantitative roles or academic careers.

Progression & Future Opportunities

Graduates of the Financial Mathematics with Professional Placement MSci (Hons) at Queen Mary University of London (QMUL) are well-prepared for careers such as quantitative analyst, risk analyst, financial engineer, investment analyst, or actuarial consultant. The professional placement provides valuable practical experience, giving students a strong advantage in entering finance, banking, insurance, and investment sectors.

Why This Degree Opens Doors:

University‑supported employability services: The QMUL School of Mathematical Sciences offers dedicated careers support, including professional placement guidance, CV and application coaching, interview preparation, and networking opportunities.
Strong employment record & starting salary: Many graduates secure employment or further study within six months of graduation, with typical starting salaries around £32,000–£35,000, reflecting the practical experience gained during placement.
Access to industry-leading employers: Graduates have connections with leading firms such as J.P. Morgan, Goldman Sachs, Morgan Stanley, HSBC, Deloitte, and KPMG, often leveraging placement experience for graduate roles.
Accredited, high‑quality academic training with long-term value: The programme combines advanced mathematics with financial theory, stochastic modelling, computational finance, and risk management, equipping students with skills that remain highly relevant across financial industries.
Professional placement experience: The integrated placement provides real-world application of mathematical finance skills, practical problem-solving experience, and professional networking opportunities prior to graduation.
Diverse graduate outcomes: Graduates enter roles in quantitative finance, investment banking, risk management, financial modelling, and actuarial work, both in national and international organisations.

Further Academic Progression:
After completing the MSci, graduates may pursue further studies such as Master’s or doctoral programmes in quantitative finance, financial mathematics, computational finance, risk management, or applied mathematics. They may also undertake professional qualifications such as CFA, FRM, or actuarial certifications, further enhancing career prospects.