BSc Mathematics with Statistics for Finance

3 Years On Campus Bachelors Program

Imperial College London

Program Overview

This three-year undergraduate degree combines rigorous mathematical theory with statistical methods applied specifically to finance and risk modelling. It is ideal for students who enjoy both abstract mathematics and applied quantitative work, and who want to pursue careers in quantitative finance, financial analytics, or risk management.

Curriculum Structure

Year 1:
The first year builds a strong foundation in mathematics and statistics. Core modules include Analysis 1, Linear Algebra and Groups, Calculus and Applications, Probability and Statistics, Introduction to Computation, and An Introduction to Applied Mathematics. These courses develop essential problem-solving, analytical, and computational skills while transitioning you to university-level mathematics.

Year 2:
In the second year, you advance your skills in mathematics and statistics through modules such as Analysis 2, Linear Algebra and Numerical Analysis, Multivariable Calculus and Differential Equations, Probability for Statistics, and Statistical Modelling 1. Optional modules and the I-Explore project allow you to start specialising toward finance and applied statistics.

Year 3:
The final year focuses on advanced finance-related mathematics and statistics. You select at least six modules from the finance/statistics stream, such as Consumer Credit Risk Modelling, Applied Probability, Time Series Analysis, Stochastic Simulation, and Mathematical Finance: Option Pricing. Additional modules from a broader mathematics/statistics list can also be taken. A major research project allows you to apply your learning to a practical finance-related problem.

Focus areas: Financial mathematics and modelling, applied statistics for finance, probability and stochastic methods, risk modelling, numerical analysis

Learning outcomes: Develop advanced reasoning and proof techniques, apply statistical and quantitative modelling in finance, analyse and solve complex financial problems, and prepare for roles in quantitative finance, analytics, or postgraduate study

Professional alignment (accreditation): Delivered by Imperial’s highly respected Department of Mathematics, ensuring the programme is recognised by employers in finance, analytics, and quantitative sectors

Reputation (employability rankings): Graduates are highly employable, with many moving into highly skilled roles in finance, analytics, or continuing to postgraduate study

Experiential Learning (Research, Projects, Internships etc.)

The BSc Mathematics with Statistics for Finance at Imperial College London is designed to combine rigorous mathematical theory, applied statistics, and financial modelling to prepare you for careers in finance, data analytics, and quantitative research. The programme balances abstract reasoning with real-world applications, giving you both the analytical depth of a mathematician and practical skills in finance and statistics.

Experiential Learning

Here’s how the programme translates theory into practical skills:

Computational and Programming Tools – From the first year, you gain hands-on experience with mathematical and statistical computation using software such as MATLAB or Maple, supporting modelling and analysis tasks.
Individual Research/Project Assignments – Early-year projects allow you to choose a topic, investigate it, and present your findings, building independent research and presentation skills.
Group Research Projects – Collaborative projects in later years enable you to apply mathematical models and statistical techniques to financial problems, enhancing teamwork and analytical communication.
Specialised Optional Modules in Finance and Statistics – In the later years, you can focus on modules such as applied probability, statistical modelling, time-series analysis, survival models, and credit risk, giving you hands-on experience with real-world financial data and models.
Problem Classes, Seminars, and Independent Study – Structured tutorials and problem-solving sessions allow you to analyse real examples, write reports, perform computations, and collaborate with peers to solve complex problems.
Exposure to Real Financial Applications – Modules are designed around practical scenarios in finance and risk management, giving you a clear understanding of how mathematical and statistical methods are applied in industry.
Dedicated Study Spaces and Support – Access to computing labs, collaborative study areas, and departmental support helps you develop both independent and team-based problem-solving skills.

This integration of theory, statistical analysis, computation, and finance ensures that graduates leave with both the intellectual rigour and practical experience required for careers in finance, data science, analytics, and quantitative research.

Progression & Future Opportunities

The BSc Mathematics with Statistics for Finance at Imperial College London combines rigorous mathematical and statistical training with a strong focus on financial applications. Graduates develop the analytical, quantitative, and computational skills required to solve complex problems in finance, risk management, and investment analysis. Typical career paths include Quantitative Analyst, Risk Analyst, Financial Modeller, and Data Scientist in Finance.

Progression & Future Opportunities:

University services: Imperial’s Careers Service offers specialised support for finance-focused mathematics students, including one-on-one career coaching, internship placements, employer networking events, and access to alumni in top financial institutions.
Employment stats & salary figures: About 89% of mathematics graduates are employed or in further study within 15 months of graduation. Starting salaries for graduates in quantitative finance typically range from £45,000 to £55,000, reflecting the high demand for mathematically skilled finance professionals.
University–industry partnerships: The programme benefits from Imperial’s strong connections with leading banks, hedge funds, investment firms, and consultancies, providing students with internship opportunities, real-world projects, and networking with industry experts.
Long-term accreditation value: While not formally accredited, the Imperial College London reputation, combined with specialised training in financial mathematics and statistics, provides strong professional recognition and a solid foundation for Chartered or professional finance qualifications.
Graduation outcomes: Graduates are highly sought after by investment banks, trading firms, consulting companies, financial software firms, and regulatory agencies. Many also progress to advanced study or research in quantitative finance, risk analytics, or data science.

Further Academic Progression:
After completing the degree, students can pursue a Master’s or PhD in Financial Mathematics, Quantitative Finance, Risk Analytics, or Data Science, building on their solid mathematical and statistical foundation. The programme also equips students to undertake professional certifications such as CFA (Chartered Financial Analyst) or CQF (Certificate in Quantitative Finance), supporting advanced careers in finance and analytics.