BSc Finance: Data Science
About this course
Finance and data science is a combination that sits at the cutting edge of what financial markets and institutions are doing with quantitative analysis. Financial markets generate enormous quantities of data, and the ability to apply machine learning, statistical modelling, and computational methods to that data is increasingly central to trading, risk management, investment analysis, and regulatory compliance. At the University of Exeter, the BSc Finance: Data Science is a three-year full-time programme that includes a sandwich year, a year abroad, and work placement, giving you substantial professional and international experience alongside a technically demanding academic curriculum. Exeter is also a partner of the CQF Institute, a globally recognised body in quantitative finance. The programme develops a rigorous foundation in financial theory and data science methods simultaneously. Financial content covers asset pricing, portfolio theory, derivative instruments, risk management, and the microstructure of financial markets, giving you a deep understanding of what financial data represents and why it matters. The data science component develops your skills in programming, statistical modelling, machine learning, and the computational methods used to extract insight from large financial datasets. The partnership with the CQF Institute provides access to a professional community in quantitative finance and the benefits of membership, which supplement the academic curriculum with professional development resources. The sandwich year and year abroad provide direct experience of international financial environments and the professional contexts in which these skills are applied. Graduates of this programme are exceptionally well positioned in the quantitative finance jobs market. Quantitative analyst (quant), data scientist in financial services, risk analyst, algorithmic trader, financial engineer, and investment analyst are among the most direct career paths. The combination of financial knowledge and data science capability is valued by investment banks, hedge funds, asset managers, consultancies, central banks, and financial regulators. Many graduates go on to postgraduate study in quantitative finance, financial mathematics, machine learning, or statistics, including programmes at some of the world's leading institutions in this field. The professional experience provided by the sandwich year and the CQF Institute partnership gives graduates a significant advantage in competing for highly sought-after roles.
Syllabus & Modules
Typical curriculumStudent Satisfaction
National Student Survey - 340 respondents (66% response rate)
Similarly Ranked Alternatives
What comes next? 🎓
Choosing the right university starts with choosing the right school. Explore transparent, data-driven school profiles powered by official DfE statistics.
Explore Schools on WhatSchool.ai →