Build data science skills for real-world economic policy
An introduction to SOAS's MSc in Data Science and Economic Policy, which combines hands-on training in AI, machine learning, and coding with direct pathways to internships and co-supervised research with some of the world's leading international institutions.
Artificial intelligence (AI) and machine learning (ML) are increasingly shaping how policy problems are analysed, how economic and development programmes are evaluated, and how evidence is translated into public action. Yet many prospective students remain uncertain about how to enter this field, particularly when they do not come from a background in computer science, advanced mathematics, or quantitative economics.
The MSc in Data Science and Economic Policy at SOAS University of London offers a clear route into that space. It is a one-year, on-campus master’s programme beginning in September 2026, designed for students who want to combine economic policy training with applied data science tools.
Miguel Niño Zarazúa, the programme convenor of MSc Data Science and Economic Policy, emphasised the unique features of the programme:
“The programme is designed for students who want to develop technical skills in machine learning and AI while remaining grounded in economic policy analysis. The MSc provides a framework through which students can build coding and quantitative skills over the course of the degree. This makes the programme particularly attractive to applicants from social sciences, development studies, public policy, or other interdisciplinary backgrounds.”
The curriculum reflects this logic of gradual progression. Compulsory modules such as Statistical Methods and Machine Learning provide a foundation in probability theory and statistics, whereas Perspectives in Economic Theory and Policy is designed to give foundations in microeconomics and macroeconomics for students without a prior background in economics.
These modules, together with Programming for Data Science and Big Data Analytics and AI, establish the central pillars of the degree: coding, quantitative methods, machine learning, AI, and economic theory. Across this general structure, students are introduced to R and Python coding, application programming interfaces, scripting, probability and statistics, methods for handling large-scale and unstructured data, the use of machine learning algorithms, and the interpretation of model outputs in economic policy analysis. The value of this design lies in the way it combines technical skills with a clear policy focus.
Guided options that allow for specialisation
A further strength of the MSc is the way it balances structure with flexibility. Alongside the compulsory modules, students take four guided optional modules, allowing them to shape the degree around their developing interests and strengths. Available options include technically oriented modules such as Econometrics with R coding, Advanced Econometrics with R coding, Evaluation Methods for Economic Policy, Data Management and Visual Analytics, Applied Issues in Machine Learning, and Research Methods.
A distinctive feature of the programme is the opportunity for regional specialisation, through modules such as Structural Change and Economic Development in Africa, Political Economy of Development and Change in the Middle East, Economic development in the Asia Pacific region, and China and World Development. Together, these options allow students both to deepen their quantitative and technical skills and to develop regionally grounded expertise.
A programme that builds towards independent applied work
The overall structure of the MSc is especially effective because it culminates in substantial independent work. The degree includes a 60-credit supervised research project, delivered alongside the taught component and completed over Semester 2 and the summer period. The project culminates in a 10,000-word dissertation submitted in September.
This dissertation component is important for two reasons. First, it gives students the opportunity to consolidate the technical and conceptual skills developed across the taught modules. Second, it enables them to apply those skills to an original question of their own, thereby moving from classroom-based training to a more autonomous mode of learning. For students entering the field from non-technical backgrounds, the progression from structured learning to independent research is particularly formative.
Opportunities to engage with global leaders
Students are eligible to apply for the co-supervised master's dissertation programme, which brings them into contact with members of the Department of Economics and leading experts from the World Bank, the International Trade Centre, the United Nations Industrial Development Organisation, the United Nations Conference on Trade and Development, and the International Labour Organisation. They are also eligible to apply for three-month remote internships at the World Bank after completing their dissertations. Together with access to research seminars and the possibility of part-time research assistant roles within the department, these opportunities strengthen the programme’s connection to wider research and policy networks.
Teaching formats that support skills development
The programme is delivered through a combination of lectures, seminars, and workshops. This matters because the acquisition of data science skills typically requires more than passive exposure to theory. Students need opportunities to practise coding, work with data, interpret outputs, and develop confidence through applied exercises.
The inclusion of workshops alongside lectures and seminars offers a teaching structure designed to support that kind of active learning. In that respect, the MSc is not simply organised around the transmission of knowledge, but around the gradual development of technical and analytical capability. Together, these elements strengthen the degree’s professional orientation.
The timetable for applications
Applications for postgraduate taught programmes beginning in September 2026 are open, and the application deadline for master’s programmes is 31 July 2026.
Applicants to the programme are eligible to apply for the SOAS New Programme Scholarships. These scholarships offer £10,000 fee waivers for eligible overseas applicants, with a scholarship deadline of 29 May 2026 at 12 noon UK time.
Header image credit: Paul Cuoco via Unsplash.
