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Data Science and Public Policy (Political Science) 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. Co-taught by UCL Economics and Political Science, this course will equip you as a policymaker to translate this wealth of information into useful insight, using cutting-edge data-science methods, rich technical skills, and detailed knowledge about economic and political processes.

UK students International students
Study mode
Full-time
UK tuition fees (2026/27)
£28,900
Overseas tuition fees (2026/27)
£39,200
Duration
1 calendar year
Programme starts
September 2026
Applications accepted
All applicants: 20 Oct 2025 – 26 Jun 2026
Applications close at 5pm UK time

Applications open

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Entry requirements

A minimum of an upper second-class Bachelor's degree from a UK university; or an overseas qualification of an equivalent standard. All applicants must provide evidence of successfully completing at least one advanced module in quantitative methods, statistics, data science or econometrics during their Bachelor's degree. Applicants are asked to upload the syllabus of their advanced module(s) in quantitative methods with their application.

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 course 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 Political Science route delves deeper into public policy formation and implementation, while the Economics route (see the separate Graduate Prospectus entry) further explores modern quantitative economic analysis. 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, this programme is custom-built for people who are passionate about studying public policy, and who want to develop the skills required to lead on economic quantitative analysis and policy-making for the future.

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 political science and economics through which you will develop a strong understanding of key issues in public policy formation, development and analysis. 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 such as:

  • 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)

Since the start of the MSc Data Science and Public Policy in 2022, graduates have gone onto a variety of roles, such as data analysts for the international organisations and consultancy firms; research analysts for NGOs and think tanks; and reporting analysts for banks and regulators.
 
(Internal Alumni Survey)

Employability

The programme is designed to teach you the knowledge and skills required to provide insight into important questions in public policy using advanced statistical methods. A series of in-depth substantive modules, delivered by economists and political scientists, will provide you with the analytical tools to think deeply about important questions in policymaking. The methodological training will enable you to understand and, crucially, apply cutting-edge quantitative methods to real-world problems. Our research-based curriculum promotes a variety of research skills, which will enable you to understand, and contribute to, quantitative analyses of public policy.

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 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; 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.

While week to week schedules will vary, students can expect to spend 10 hours in lectures, 8 hours in tutorials or practicals, up to 4 hours in advisory or supplemental engagement sessions, and about 15 hours working on independent study and research. In total, students will spend approximately 35–40 hours a week on this programme, equivalent to full time employment.

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 Political Science Route curriculum delivers highly structured training in applied data science as well as substantive instruction in political science.

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. You will take three core data science modules and one political science module in the first term:

  • Statistical Learning for Public Policy. In this compulsory module, which runs throughout Terms 1 and 2, you will be introduced to a wide range of statistical methods in data science, from classical statistical methods to recent advances in machine learning. The module emphasizes practical applications, enabling you to develop the skills needed to build and interpret models for real-world data. You will engage with diverse datasets, acquiring practical experience in analysing structured and unstructured data.
  • Statistical Programming for Social Data Science. In this module, you will learn foundational skills in statistical programming, in particular for the R programming language, as well as essential Python. The module will introduce you to foundational concepts in programming, principles of good data management, and an introduction to data visualisation. The module will cover a variety of issues that are central to practical data analysis work. Topics on this module may include data collection and cleaning; data exploration; version control; visualization; object-oriented programming; web-scraping.
  • 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.
  • The Politics of Public Policy. In this core module you will study the social dilemmas that are common to many public policy challenges, such as externalities, and collective action and coordination problems; and a series of challenges faced by political actors intending to implement good governance, including features of the political process that affect incentives (such as electoral and legislative institutions), and more fundamental issues that can lead to suboptimal outcomes (such as information problems and commitment problems). Additionally, you will learn some of the key analytical skills required for rigorously analysing the politics of public policy, including basic game theory and decision theory. 

Term 2

In the second term, you will continue to study the Statistical Learning module, and will cover some cutting-edge methods in data science. In addition, you will be able to concentrate on the particular data-science subfield that interests you the most. You will also take two further options modules from political science:

  • Statistical Learning for Public Policy (continued from Term 1).
  • 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; machine learning in economics; and data science theory.
  • One elective from a set of political science modules. The exact modules available each year are subject to change, but these may include law and regulation; policy implementation; making policy work; policymaking and regulation in Europe; global public policy; international political economy; and public management.
  • One further elective from the either set of data science or public policy modules.

Dissertation

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

Compulsory modules







Optional modules

Data Science Theory













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 (Political Science).

Accessibility

The department will endeavour to make reasonable adjustments for students with disabilities, including those with long-term health conditions, neurodivergence, learning differences and mental health conditions. This list is not exhaustive. If you're unsure of your eligibility for reasonable adjustments at UCL, please contact Student Support and Wellbeing Services.

Reasonable adjustments are implemented on a case-by-case basis. With the student's consent, reasonable adjustments are considered by UCL Student Support and Wellbeing Services, and where required, in collaboration with the respective department.

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information about support available can be obtained from UCL Student Support and Wellbeing Services.

For more information about the department and accessibility arrangements for your course, please contact the department.

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Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2026/27) £28,900
Tuition fees (2026/27) £39,200

Additional costs

For full-time and part-time offer holders with a fee status classification of UK, a fee deposit will be charged at 2.5% of the first year fee.

For full-time and part-time offer holders with a fee status classification of Overseas, 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.

For in-person teaching, 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 £119.90. This price was published by TfL in 2025. 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

Michael Curtis Bursary

Deadline: 25 June 2026
Value: £15,000 (1 year)
Criteria Based on financial need
Eligibility: UK

Sabina Kamber Bursary

Deadline: 25 June 2026
Value: £15,000 (1 year)
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 course 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 (Political Science) at graduate level
  • why you want to study Data Science and Public Policy (Political Science) 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 and route
  • where you would like to go professionally with your degree
  • details of your quantitative skills, such as in probability and statistics and data analysis
  • any skills you have with spreadsheets, statistical software, 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 courses (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: 2026-2027

Apply for this course

Got questions? Get in touch

Economics
Economics

economics.dspp@ucl.ac.uk

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