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Data Science and Public Policy (Economics) MSc

London, Bloomsbury

The size and complexity of digital information now available has the potential to improve how we understand, design, implement and evaluate effective public policy. On the economics route of this cross-disciplinary MSc, you’ll develop the expertise required to provide insight into – and help solve – important societal issues using advanced statistical and data science methods, computer programming, machine learning and detailed knowledge about economic and political processes.

UK students International students
Study mode
Full-time
UK tuition fees (2025/26)
£36,500
Overseas tuition fees (2025/26)
£36,500
Duration
1 calendar year
Programme starts
September 2025
Applications accepted
All applicants: 14 Oct 2024 – 01 May 2025
Applications close at 5pm UK time

Applications open

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Entry requirements

A minimum of an upper second-class Bachelor's degree in Economics with a significant quantitative component from a UK university, or an overseas qualification of an equivalent standard. Applicants with a qualification of an equivalent standard in another quantitative discipline, e.g. statistics, mathematics, or physics, may also be considered.

Applicants whose studies for their undergraduate degree have been undertaken wholly or mainly at a university located outside the UK must supply GRE General Test scores and demonstrate competence in English at UCL’s Advanced level before the start of the course and preferably at the time of application. The quantitative GRE score must be 162 or above (post-August 2011 scores). If you studied either an undergraduate or postgraduate degree wholly or mainly at a university in the UK you do not need to provide a GRE score.

Relevant practical or work experience in a related field may also be taken into account. For example, this might include: i) at least two years of experience working in a public sector organisation, a think tank, an international-governmental organisation, or in a public-policy consultancy role; or ii) at least two years of experience working in a data-science role

The English language level for this programme is: Level 4

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree


The rapid expansion and increased availability of quantitative data in recent years presents policymakers with great challenges and opportunities alike. The vast complexity of digital information at our fingertips can provide us with the means to understand, design, implement, and evaluate effective public policy. However, translating this wealth of information into useful insight requires a deep understanding of cutting-edge data-science methods, rich technical skills, and detailed knowledge about economic and political processes. The Data Science and Public Policy MSc is defined by two routes: one for Economics, and one for Political Science. You’ll receive expert insight and training in applied data-science methods and economic and political processes in both routes, via three compulsory modules shared by both pathways.  

The Economics route further explores modern quantitative economic analysis, while the Political Science route (see the separate Graduate Prospectus entry for information) delves deeper into public policy formation and implementation. Each route has its own set of entry requirements to reflect the emphasis of that route. You can apply for a place on either the Economics or Political Science route of this programme, according to your experience and career direction.

Who this course is for

Taught by experts in quantitative social science, the degree is designed for people who are passionate about studying public policy, and who want to develop the skills required to play a leading role in the quantitative analysis of policymaking in the years to come.

Read about what it takes to study for a Master's at UCL

What this course will give you

This programme will provide you with intensive training in applied data-science methods, computer programming, statistics, and machine learning, with a focus on applying these tools to questions in public policy. You will also take specialised modules in economics through which you will develop a strong understanding of key issues in public policy formation, development and analysis using economic theory. The programme features a combination of compulsory modules and options, enabling you to chart your own path.

Read about what you'll get out of a graduate programme

The foundation of your career

Alumni from current MSc programmes in UCL's Political Science and Economics departments have gone on to attain employment in diverse areas:

  • The civil service (e.g., HM Treasury, local government).
  • International institutions (e.g., the European Commission, the UN)
  • Central banks (e.g., Bank of England and European Central Bank)
  • Research (e.g., policy and economics-related institutes akin to the Institute of Fiscal Studies, the Institute of Government etc.)
  • Consultancy (e.g., within the Big Five), and throughout the financial sector.

(Graduate Outcomes survey 2017-2022)

Employability

The programme is designed to enhance career prospects by giving students transferrable skills attractive to employers such as: 

  • Theoretical and analytical thinking about important questions in policymaking.
  • Methodological training to understand apply cutting-edge quantitative methods to real-world problems.
  • Research skills to understand, and contribute to, quantitative analyses of public policy.

You will also learn to solve problems and issues and to build positive working relationships. This means you will be a good team player, who can manage and delegate to others and take on responsibility.

Networking

Students at UCL Economics have invaluable opportunities to meet world-leading academics and experts in the subject field during their studies. Drawing on its myriad close relationships with organisations such as the Institute for Fiscal Studies, UCL Economics has collaborative and consultative relationships with government, the policy sphere and broader public and financial sectors.

The department has a rich programme of internal and external seminars, student camps, the incredible, student-run Economists Society and an annual Careers Week which brings together our vibrant and global alumni community, industry speakers and skills workshops. These deep, rich connections and collaborations mean our students do more than study here, they springboard to new levels in their careers.

Teaching and learning

The programme includes a variety of teaching and learning methods, designed to develop different critical skills. This includes lectures, small-group and faculty-led seminars and technical training through regular computer labs. You will produce essays, policy briefs and research papers that make use of cutting-edge approaches in data science.

You will undertake a range of formative and summative assessments. Formative assessments include in-lecture practical exercises and discussions; applied problem-sets; and in-class quizzes. The programme will also make use of extensive computer-lab-based problem sets which will help to develop and test your practical coding skills.  Summative assessments include essays, reports and exams. 

Contact time takes various forms:

  • Lectures.
  • Seminars.
  • Project supervision.

The credit value of the module indicates the total learning hours you will spend to achieve its learning outcomes. One credit is often equated to 10 hours of notional learning, which includes all contact time, self-directed study, and assessment.

Each module on the programme will involve approximately three hours of contact time per week (spread across lectures and seminars), and at least eight hours of private study per week.

While week to week schedules will vary, students can expect to spend 25% of their time in lectures, 20% in tutorials or practicals, up to 10% in advisory or supplemental engagement sessions, and about 45% working on independent study and research.

Your research project/dissertation will take up a good portion of your time in the programme, particularly towards the end. The learning hours will mainly be spent researching and writing your final dissertation. During the research and writing stages you will also have regular contact with your supervisor(s) who will guide and support you throughout your work.

Modules

The one-year Economics Route curriculum delivers highly structured training in applied data science as well as substantive instruction in economics.  

Core curriculum  

Summer

In the summer before Term 1, you will complete an online, self-paced foundation module in Maths and Stats. You will take the final exam on the Maths and Stats module in the first week of term. Although the Maths and Stats exam mark does not count toward the Data Science and Public Policy degree in a formal sense, the exam provides feedback on your readiness for the technical demands of the Data Science and Public Policy MSc programme. You will also take an online Data Camp, which is a short course to help you brush up or learn the fundamentals of R before joining in September, and prepare for the programming needs of the MSc.

Term 1

The first term will provide you with foundational data science and programming skills that are required for modern quantitative analysis. In addition, you will learn skills within a topic in economics as chosen by you: 

  • Statistical Learning for Public Policy. This compulsory module, which runs throughout term one and term two, provides an introduction to a variety of statistical methods in data science, as well as many recent advances in machine learning. You will learn about the mathematical foundations of these approaches, and, crucially, will also gain experience in applying the methods to real-world public policy datasets.  
  • Statistical Programming for Social Data Science. In this module you will also develop your skills in data management, visualization, and statistical computation and will become well-versed in the R programming language.  
  • Data, Evidence and Public Policy. In this module you will study how data science methods are used in, and are forcing changes upon, the contemporary policymaking process. You will be taught by leading quantitative social science researchers and data science practitioners in government and industry, to explore how “big data” is used in public policy. You will also address some of the ethical and legal challenges that have arisen in response to the growth of data science approaches in this field. 
  • One elective in economics: You can choose between studying Microeconomics, Macroeconomics, or Econometrics. This allows you to focus on the substantive area of economic public policy that interests you the most and  creates a pathway  for further study in your chosen area for the rest of the MSc year.

Term 2

In the second term, you will write your dissertation proposal and continue to study in the Statistical Learning module. In addition, you will take Machine Leaning in Economics where you will apply the skills obtained from Statistical Learning to important economic issues. You will also be able to further explore the particular data-science area that interests you the most through a data science options module. Finally, you will continue with the economics pathway you had chosen in Term 1, by taking an economics options module in the sub-field of your choice:  

  • Statistical Learning for Public Policy (continued from Term 1). 
  • Machine Learning in Economics. This module will cover applications of machine learning methods and other high-dimensional estimation methods for causal inference in economics. The applications include Instrumental Variable models, treatment effects, policy evaluation, counterfactual analysis, estimation of structural models, panel data models.  
  • One elective from a set of data science modules. The exact modules available each year are subject to change but may include quantitative text analysis; causal inference;  and data science theory. 
  • One elective from a set of economics modules. The exact modules available each year are subject to change and will depend on the pathway you are following from Economics your module selection in Term 1. Modules may include time-series econometrics; macroeconomic policy; behavioural economics; health economics; environmental economics; public microeconomics; and economics of development. 

Dissertation

Alongside your selected modules, you will complete an independent research project under the supervision of an academic in the Department of Economics. Your project will apply the data science skills developed throughout the year to answer a substantive question of public policy of your own choosing, subject to the agreement of your dissertation supervisor.

Compulsory modules










Optional modules




Environmental Economics: Principles and Policy









Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Data Science and Public Policy (Economics).

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support and Wellbeing Services team.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2025/26) £36,500
Tuition fees (2025/26) £36,500

Additional costs

For Full-time and Part-time offer holders a fee deposit will be charged at 10% of the first year fee.

Further information can be found in the Tuition fee deposits section on this page: Tuition fees.

There are no additional costs for this degree.

UCL’s main teaching locations are in zones 1 (Bloomsbury) and zones 2/3 (UCL East). The cost of a monthly 18+ Oyster travel card for zones 1-2 is £114.50. This price was published by TfL in 2024. For more information on additional costs for prospective students and the cost of living in London, please view our estimated cost of essential expenditure at UCL's cost of living guide.

Funding your studies

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

See all the ways you can fund your studies

Aziz Foundation Scholarships in Social and Historical Sciences

Value: Full tuition fees (equivalent to 1yr full-time) (1yr)
Criteria Based on financial need
Eligibility: UK

Next steps

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

There is an application processing fee for this programme of £90 for online applications. Further information can be found at Application fees.

When we assess your application, we would like to learn:

  • why you want to study Data Science and Public Policy (Economics) at graduate level
  • why you want to study Data Science and Public Policy (Economics) at UCL
  • what particularly attracts you to the chosen programme and route
  • how your academic and professional background meets the demands of this challenging programme
  • where you would like to go professionally with your degree
  • details of your quantitative skills, such as in mathematics, calculus, probability and statistics, and linear algebra
  • any skills you have with spreadsheets, statistical software, mathematical programming or working with data

Together with the essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2025-2026

Apply for this course

Got questions? Get in touch

Economics
Economics

economics.dspp@ucl.ac.uk

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