Mathematics and Statistics with Data Science

Mathematics and statistics with data science is a degree that places rigorous quantitative training at the centre of one of the defining professional skills of the present decade. Mathematics provides the formal foundations: analysis, linear algebra, probability theory, and optimisation, all of which underpin both the theoretical and applied dimensions of data science. Statistics adds the framework for drawing defensible inferences from data, managing uncertainty, and building models that generalise beyond the sample.

Data science applies these to the practical challenge of extracting insight from the large and messy datasets that modern organisations generate.

At the University of Reading, this three-year, full-time programme includes a sandwich year, a year abroad, and a work placement, making it a degree with unusually rich experiential learning built in. The placement gives you direct experience of working with data in a real organisation before your final year, while the year abroad allows you to study mathematics and statistics in a different academic environment, broadening your perspective and developing your independence. Reading's mathematics department is research-active, and the programme develops both theoretical understanding and practical computational skill.

You will study pure and applied mathematics, probability and statistical inference, regression and multivariate analysis, machine learning, and the programming and data handling skills that data scientists use in practice. A typical entry tariff of 136 UCAS points reflects the mathematical preparation expected.

The combination develops both the theoretical rigour that sets mathematically trained data scientists apart and the practical skills to work with real data.

Graduates work in data science, quantitative research, financial modelling, actuarial roles, statistical consulting, machine learning engineering, and the civil service analytical function. Postgraduate study in statistics, data science, or machine learning is also a well-trodden route.