Mathematics with Data Science

Mathematics and data science are increasingly inseparable. The methods that allow organisations to extract meaning from large volumes of data, to build predictive models, and to make better decisions are mathematical at their core. Statistics, linear algebra, calculus, probability, and computational methods are the building blocks of machine learning, data analysis, and the broader toolkit of the modern data scientist.

A degree that combines rigorous mathematical reasoning with practical data science skills prepares graduates for one of the most in-demand roles in the contemporary economy.

At City St George's, University of London, this three-year full-time programme brings together core mathematical training with a focus on data science methods and their applications. You will study pure and applied mathematics alongside modules in statistics, programming, machine learning, and data analysis, developing the ability to move fluently between mathematical theory and computational practice. The programme includes a sandwich year and a work placement, giving you substantial professional experience in an industry or research setting before you graduate.

London's position as a centre for finance, technology, and business means there are rich opportunities for placement and professional networking within reach of the campus.

You will develop strong problem-solving skills, mathematical fluency, programming proficiency, and the ability to communicate quantitative insights clearly. These capabilities are valued across a wide range of sectors.

Graduates go on to roles as data scientists, data analysts, quantitative analysts, software engineers, machine learning engineers, statisticians, and business intelligence analysts. The combination of mathematical depth and data science application is particularly valued in finance, technology, healthcare, retail, and government. Postgraduate study in mathematics, statistics, or data science is also a well-travelled route.