Economics and Data Science

Economics and data science is a combination designed for a world in which the most important economic questions increasingly require large-scale data analysis to address them. Economics provides the theoretical frameworks for understanding how markets, institutions and policies function and what their effects on individuals and societies are. Data science provides the computational and statistical methods to work with the vast quantities of information that modern economies generate, turning raw data into evidence that can inform decisions at every level from government policy to corporate strategy.

At Royal Holloway, University of London, this three-year programme gives you a rigorous grounding in both disciplines, developing the analytical depth of economics alongside cutting-edge skills in data analysis and interpretation. You will study microeconomics, macroeconomics and econometrics alongside data science methods including programming, machine learning, statistical modelling and data visualisation. A sandwich placement year provides substantial professional experience in an economics or data-related environment, and a year abroad adds international perspective to your studies.

Work placement opportunities are integrated throughout the programme, connecting your academic training to real-world applications.

Graduates in economics and data science are exceptionally well placed in the jobs market. Roles in economic analysis, policy research, financial data analysis, management consultancy, central banking, financial services and technology companies with economics functions are all natural destinations. The data science component adds particular value for roles that involve working with large datasets, building predictive models or contributing to evidence-based decision-making in any sector.

Many graduates pursue postgraduate study in economics, data science, finance or related fields. The combination of economic reasoning and computational skill is among the most powerful credentials available for graduates entering data-driven professional environments.