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Finance with Data Science MSc

London, Canary Wharf

This is the programme information for 2026/27 entry

If you require details of the previous year's programme, Finance with Data Science MSc (2025/26), click here

Important notice

Please note that the UCL graduate application portal will be unavailable from 5pm (UK time) on Friday, 5 December until 10am (UK time) on Monday, 8 December. Disruption may occur outside of these anticipated times. Applications through other institutions should remain unaffected. Please accept our apologies for any inconvenience caused by this interruption of service.

UK students International students

Study mode

Full-time

UK tuition fees (2026/27)

£48,250

Overseas tuition fees (2026/27)

£48,250

Duration

1 calendar year

Programme starts

September 2026

Applications accepted

Applicants who require a visa: 20 Oct 2025 – 26 Jun 2026

Applications close at 5pm UK time

Applications open

Applicants who do not require a visa: 20 Oct 2025 – 28 Aug 2026

Applications close at 5pm UK time

Applications open

Apply for this course

Entry requirements

A minimum of an upper-second class Bachelor's degree from a UK university or an overseas qualification of an equivalent standard in one of the following subjects: economics, finance, mathematics, econometrics and statistics or a combination of these disciplines. Degrees from other disciplines may be considered provided the background is sufficiently quantitative. Applicants are not required to submit a Graduate Record Examinations (GRE) or Graduate Management Admissions Test (GMAT) result as part of their initial application. However, submitting a score of at least 165 in the quantitative section of the GRE will add weight to the application. Applicants may also wish to submit GMAT (or GMAT Focus) results, but we will not provide guidance in terms of minimum score.

The English language level for this course is: Level 2

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

Data science is becoming increasingly important in the finance industry, as companies seek graduates whose main expertise is in finance but who also have a high level of data science literacy and skills.

The Finance with Data Science MSc will equip you with the skills required to make data-driven decisions as a finance specialist and stand out in the job market. You'll learn to collaborate and contribute on the technical aspects of projects, analyses, and decisions with colleagues and, in particular, with data science experts.

The programme is delivered by The UCL School of Management and UCL's Department of Economics. It has been specifically designed based on world-class research expertise in finance, data science, econometrics, and economics.

You'll leave this programme ready to secure a position in major global financial hubs, whether at a bulge bracket investment bank, hedge fund, or pioneering data-driven finance start-up.

Who this course is for

The Finance with Data Science MSc is ideal for individuals with a robust quantitative background who want to kickstart a high-profile career in quantitative finance or who wish to advance on an established path within the sector.

You are expected to have a strong quantitative background on this programme, which is data-driven throughout, and you will work extensively with real-world financial data (e.g., from Bloomberg terminals and Refinitiv). You will handle and analyse this data with a combination of standard software (e.g., Microsoft Excel) and Python programming.

No prior knowledge of coding is required, but you should be highly motivated to develop these skills right from the start of the pre-sessional module. We expect a great deal from our students, so if you choose to study with us, you can expect to be working hard, challenging yourself as we challenge you, and regularly placing yourself outside your comfort zone.

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

What this course will give you

This degree programme offers the following opportunities and benefits:

Equip yourself with the skills of a finance specialist with a high level of data science literacy to collect and manipulate data and use it to perform formal analysis and produce reports using data visualisation, all of which can inform strategic decisions within a financial organisation;
Learn how to demonstrate critical thinking and problem-solving ability in the context of questions related to finance, a skill sought out by employers in the global finance industry;
Study at a top 10 global university (QS World University Rankings 2025);
AACSB accredited: Recognised globally as a hallmark of excellence in business education, ensuring high academic standards, a strong focus on research and teaching quality, and enhanced global career opportunities for graduates;
Become a part of the UCL School of Management and the UCL Department of Economics, ranked 2nd and 1st respectively in the 2021 Research Excellence Framework (REF) for producing ‘world leading’ and ‘internationally excellent’ research;
Become a part of our global alumni network;
Immerse yourself in Canary Wharf, the heart of London’s dynamic financial centre, with classes at UCL’s One Canada Square https://www.mgmt.ucl.ac.uk/about/canary-wharf. This strategic location gives you access to build a network in the financial industry;
Join a CQF Institute University Partner. The CQF Institute, the awarding body for the Certificate in Quantitative Finance, is a leading quantitative finance membership organisation with members in over 90 countries worldwide.
If you want to learn more about the programme and life at the UCL School of Management. Speak to a current student now.

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

The foundation of your career

This programme will provide you with the knowledge, understanding and skills to engage with specialist roles in the modern global financial industry. (Graduate Outcomes Survey 2017-22)

The degree prepares you for a wide range of careers, typically in a financial company, in roles that are more quantitative than MSc Finance graduates, and with a large expected exposure to computer and data scientists. Some examples include:

Credit Analyst (e.g., in a credit rating agency)
Portfolio Analyst (pathway to become a Portfolio
Manager in any asset management company)
Quantitative Analyst (e.g., in a hedge fund)
Risk Analyst (e.g., in a clearing house)
Investment Analyst (in any finance boutique)
Financial Engineer (e.g., in an investment bank to design structured products).

Employability

The MSc Finance with Data Science equips students with a powerful blend of financial expertise and data analytical skills essential in today’s data-driven economy. Graduates gain subject-specific abilities such as financial modelling, risk analysis, and coding for data analysis,as well as experience working with large datasets and financial databases. The programme also develops wider professional skills including critical thinking, communication, teamwork, and problem-solving. These capabilities are highly valued across industries such as banking, asset management, fintech, consultancy, and regulatory bodies, preparing graduates for roles that require both financial acumen and data fluency.

Networking

The programme offers an extensive schedule of networking events throughout the year:

Access a Corporate Speaker Series with leading industry experts, providing insights into current market topics and personal reflections on pursuing careers in finance.
Join alumni networking events, which can help you navigate your next steps.
Attend careers training sessions with employers and alumni events as a part of your programme and with other postgraduate students from the UCL School of Management, enabling connections across peer groups.
Benefit from the CQF institute partnership, through a wide range of additional resources, workshops, industry insight sessions, conferences and networking opportunities.
Find out more about the School of Management’s latest New Technologies & Innovation Speaker Series and Business Leader Speaker Series, designed with the support of UCL’s global network to help you develop a deeper understanding of the world of business, its challenges and opportunities, and learn directly from the experience of others at the forefront of their fields.

Accreditation

UCL School of Management is proud to be AACSB accredited – a global mark of excellence that recognises our commitment to innovative, research-led teaching, rigorous academic standards, and preparing students for impactful global careers in business and management.

Teaching and learning

The programme is delivered through a combination of lectures and interactive components.

Assessment is through written examinations, individual/group coursework, and a combination of a written report and viva for the research project.

The total number of weekly hours will vary depending on your modules and weekly activities.

In Term 1, you’ll take two modules with around 12 contact hours per week, including practical sessions, and spend approximately 14–24 hours on independent study and assessments. In Term 2, most students take four 15-credit modules, with around 12 contact hours per week and 28–48 hours of independent study. In Term 3, optional modules are delivered intensively over five weeks, with around 12 contact hours and 14–24 hours of independent study per week during that period.

Overall, you can expect to commit approximately 30–60 hours per week to the programme, combining contact time with independent learning.

For a full overview of the programme structure please visit the UCL School of Management website.

Modules

You'll study 2 core modules in Term 1, which delve into the scientific foundations of finance (covering among others the economics of financial markets, firm capital structure decisions, and investment) and introduce you to financial econometrics and data analysis using the Python coding language. No prior programming knowledge beyond the pre-sessional material is required.

In Term 2, a further 2 core modules are studied, where you'll explore additional frontier topics at the intersection of finance and data science, namely time series analysis and forecasting and big data analysis and machine learning.

An elective portfolio is offered, with 4 optional modules which can be undertaken in Term 2 and/or Term 3. This allows further customisation of learning with optional modules.

Additionally, in Term 3 and during the summer, you'll engage in the design, execution and delivery of a finance research project which will be supported by specific briefing and follow-up sessions.

Compulsory modules

Time Series Analysis and Forecasting

Big Data Analytics

Financial Econometrics and Data Science

Corporate Finance and Financial Markets

Finance with Data Science Research Project

Optional modules

Options and Derivatives

The Economics of Trading and Exchanges

Advanced Corporate Finance

Investment Strategies and Risk Management

International Finance

Behavioural Finance and Neuroeconomics

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 Finance with Data 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.

Fees and funding

Fees for this course

UK students International students

Fee description	Full-time
Tuition fees (2026/27)	£48,250
Tuition fees (2026/27)	£48,250

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.

This programme does not have any compulsory additional costs beyond the purchase of books, stationery, printing, or photocopying.

However, students are required to have a laptop. A suitable device typically costs between £600 and £1,200, depending on specifications. We also strongly recommend using an additional monitor to support your learning, especially when working with financial software, though this is optional.

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

UCL School of Management MSc Finance with Data Science Scholarships

Scholarships of up to £10,000 are available for a select number of outstanding candidates on the Finance with Data Science MSc programme in the 2026/27 academic year.

The Fulbright Commission Award

The Fulbright Commission Award is available for a US graduate student or those with equivalent experience in a relevant field to study Finance with Data Science MSc. Please note this is only available to citizens of the United States of America. Further details on the Fulbright website and the Fulbright US Student Program website.

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

: Global Finance Scholarship

Value: Up to £10,000 (1 year)

Criteria Based on academic merit

Eligibility: EU, Overseas

The Excellence Scholarship - School of Management

Value: Up to £10,000 (1 year)

Criteria Based on academic merit

Eligibility: UK, EU, Overseas

The Impact Scholarship - School of Management

Value: Up to £10,000 (1 year)

Criteria Based on both academic merit and financial need

Eligibility: UK, EU, Overseas

UCL East London Scholarship

CLOSED FOR 25/26 ENTRY

Value: Tuition fees plus £16,000 stipend ()

Criteria Based on financial need

Eligibility: UK

Women in Finance Scholarship

Value: Up to £10,000 (1 year)

Criteria Based on academic merit

Eligibility: UK, EU, Overseas

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.

A staged admissions process is in place for this course. This means that when you apply, your application will be considered with all others that have submitted before the deadline. This enables us to ensure that all applications are considered fairly and equally.

Applications submitted, and considered complete by 8 December 2025 can expect to receive a response on their application by 9 February 2026.

Applications submitted, and considered complete by 20 February 2026 can expect to receive a response on their application by 24 April 2026.

Applications submitted, and considered complete by 17 April 2026 can expect to receive a response on their application by 5 June 2026.

Non-visa nationals only: Applications submitted, and considered complete by 28 August 2026, can expect to receive a response on their application by 21 September 2026.

Please note that our 'response' may include being informed that your application is being held for further review against other applicants.

Together with essential academic requirements, your CV will attest to your academic and professional background and tell us how prepared you are to meet the challenging demands of this programme.

Please make sure your CV is accurate and provides specific information related to dates of employment or experience, positions held and company names and locations.

Submitting a personal statement is not required but can be used if you wish to communicate specific information to the admission committee.

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.

This course requires two references. Further information regarding references can be found on this Selecting your references page.

Choose your programme

Please read the Application Guidance before proceeding with your application.