Overview
Start date: September 2025
Duration: 12 months (Full-time only)
Fees: UK - £47,100 (per annum). Overseas - £47,100 (per annum). Scholarships available.
Application deadline: Applications will open on 14 October 2024 and close as follows - Applicants who require a visa: applications close on 27 June 2025 at 17:00 UK time, Applicants who do not require a visa: applications close on 29 August 2025 at 17:00 UK time.
Entry: A quantitative undergraduate degree at 2:1 Honours (or equivalent) from a recognised university. Applicants are also required to meet the Level 2 English Language requirements. Learn more.
Location: This programme is delivered at our Canary Wharf campus.
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Programme
The Master’s in Finance with Data Science is a unique programme that combines the scientific foundations of finance with the theory and practice of rigorous financial data analysis.
Data science is becoming increasingly more 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 Master’s in Finance with Data Science programme aims to equip you with the skills required to make data-driven decisions as a finance specialist and stand out in the job market.
The programme has been designed based on world-class research expertise in finance, data science, econometrics, and economics. It is highly quantitative combining theory and practice, delivered by leading faculty from the UCL School of Management and the UCL Department of Economics. Drawing on the knowledge and expertise of UCL's academic staff, you will access a rich repository of expertise to navigate real-world challenges using financial market data.
The programme is well-suited for individuals who are passionate about finance. It will equip you with the skills and knowledge essential for positions in major global financial hubs such as New York, London, and Hong Kong—whether at a bulge bracket investment bank, hedge fund, or pioneering data-driven finance start-ups.
We target to enrol a global cohort of 70 students for the 2025-2026 academic year. Since the programme is new for 2025, we do not have existing student data. However, as an indication, data from the existing MSc Finance programme can be used to represent a typical cohort for a programme of this kind.
Programme structure
The programme’s unique intersection of finance and data science allows you to explore key financial topics such as 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.
An online pre-sessional course in mathematics, statistics, accounting and introduction to programming (Python) will be provided. These are designed to ensure all students are at the required level to maximise their learning outcomes from the outset.
You will study two core modules in Term 1, which delve into the scientific foundations of finance 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, you will study two additional core modules. They focus on frontier topics at the intersection of finance and data science: time series analysis and forecasting, and big data analysis and machine learning.
In Terms 2 and 3, you will be able to customise your learning experience by selecting the optional modules that best fit your interests and aspirations.
Finally, in Term 3 and during the summer, you will work on a concrete finance research project that will allow you to showcase the data analysis skills you will have acquired. In the process, you will be supported by topic-specific briefing and follow-up sessions.
The optional modules listed are subject to change each year and are indicative only. For questions about optional modules, please contact us at: mgmt-fds@ucl.ac.uk
MODULES
Programme for Students Starting Year 1 in September 2025
| Term 1 | Term 2 | Term 3 and over the summer period |
|---|---|---|
|
Compulsory Financial Econometrics and Data Corporate Finance and Financial Markets
|
Compulsory MSIN0106 Time Series Analysis and Forecasting MSIN0208 Big Data Analytics Optional Options and Derivatives The Economics of Trading and Exchanges Advanced Corporate Finance
|
Compulsory Finance with Data Science Research Project Optional Investment Strategies and Risk Management International Finance Behavioural Finance and Neuroeconomics
|
Teaching Methods and Typical Contact Hours
The programme is delivered through a combination of lectures and interactive components. Assessment is through written examinations, individual/group coursework, and a 6,000-word research project.
In Term 1, there are two 30-credit modules. They are delivered over 10 weeks during which there are typically 6 contact hours per module (please note that this also includes practical sessions). In Term 2, both compulsory and optional modules bear 15 credits and are delivered over 10 weeks, with typically 3 contact hours per week per module. Optional modules in Term 3 are delivered over a period of 5 weeks, with typically 6 contact hours per week.
In addition, students spend approximately 7-12 hours a week for each 15-credit module (and twice as much on the 30-credit modules) on assessment and independent study to further develop the skills and knowledge covered in lectures and practical sessions.
The total number of weekly hours will vary according to the module and the weekly activities being undertaken.
How is this programme unique?
This programme is data-driven throughout and you will work extensively with real-world financial data (e.g., from Bloomberg terminals and Refinitiv), which you will handle and analyse both with basic software such as Microsoft Excel and with Python. This will help you to develop the skills required to analyse real-world problems and phenomena through an economic modelling lens and combine econometric methods and economic insight to produce data-driven solutions to finance problems.
Upon completing the programme, you will be equipped 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. You will be able 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.
UCL is also 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. This institute partnership offers a wide range of additional resources, workshops, industry insight sessions, conferences and networking opportunities as a student on the programme.
Why choose UCL?
UCL is one of the world’s best universities, consistently placed in the global top 20 in a wide variety of world rankings.
The programme is delivered jointly by the School of Management and the Department of Economics.
UCL School of Management offers carefully designed programmes to prepare future leaders in the next generation of innovation-intensive organisations. The majority of the research carried out in the UCL School of Management was rated as “world-leading” and "internationally excellent" in the 2021 Research Excellent Framework (REF), placing us second in the UK for business and management.
The UCL Department of Economics has an outstanding international reputation in key areas of current research. The Department ranked top in the UK for research environment and outputs in the field of Economics and Econometrics in the 2021 Research Excellence Framework. The REF has placed UCL Economics first for 4* world-leading research outputs and research environments, with scores of 72% and 100% respectively. The Department also placed third in its overall ranking with 65% of all indicators ranked as 4*. The Department provides students with an in-depth knowledge of cutting-edge techniques in theoretical and applied economics, utilising robust quantitative underpinnings.
Applications
Designed for individuals with a robust quantitative and mathematical background, the MSc in Finance with Data Science is the ideal programme for those pursuing a high-profile career in quantitative finance or who wish to advance on an established path within the sector.
As an MSc Finance with Data Science student, you are expected to have a strong quantitative background. 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. With this in mind, 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 finding yourself outside of your comfort zone.
Our students come from a range of academic backgrounds, including economics, finance, mathematics, econometrics and statistics. Degrees from other disciplines may be considered provided the background is sufficiently quantitative.
Application Process
Applications for the 2025/26 academic year opened on 14th of October 2024. Programmes are competitive so students are advised to apply as early as possible.
Apply to MSc Finance with Data Science
Entry Requirements
We look for students with drive, intelligence, passion, and the right aptitude. To ensure we enrol students who meet this criteria, we use the following methods to assess applications.
• A quantitative undergraduate degree at 2:1 Honours (or equivalent) from a recognised university. International students can find their international equivalency on the UCL international students website.
• Degrees in economics, finance, mathematics, econometrics and statistics are preferred. Degrees in related fields are also considered provided they are quantitative enough.
GMAT/GRE
• GMAT/GRE are not required for MSc Finance with Data Science.
• However, an outstanding GRE quantitative score (165+) adds weight to your application.
English Language Requirement
• The English language level for this programme is Level 2.
• Further information can be found on our English language requirements page.
CV
Applicants are required to submit a CV. Please make sure to provide all relevant and accurate information (exact degree title, beginning and end dates, location for professional experience, etc.)
Personal Statement
Submitting a personal statement is not required, but can be used if you wish to communicate specific information to the admission committee.
Interview
Applicants who meet the entry requirements will be reviewed. Those considered eligible for the next stage will be invited to an online video interview, with the invitation sent by email from Kira Talent.
Not sure which programme is for you?
Choosing the right programme is essential for a successful application and to ensure you maximise your time with us. We also offer an MSc Finance programme, which is a more generalist programme. The key differences are summarised in the table below.
|
|
MSc Finance with Data Science |
MSc Finance |
|---|---|---|
| Typical applicant | Aspiring finance professional with a passion for data and the will to develop cutting-edge data science and econometric skills. | Aspiring finance professional with broad interests. A typical first job title will be Financial Analyst and many graduates will aspire to taking the full sequence of CFA certification rapidly. |
| Balance and focus | A specialist finance degree that aims at providing a very high level of data science literacy. | A generalist finance degree that balances scientific foundations and the practice of finance. |
| Entry requirements | 2:1 (first preferred) | 2:1 (first preferred) |
| Quantitative skills | Outstanding quantitative skills | Excellent quantitative skills |
| GRE/GMAT | Not required, but outstanding GRE quantitative score (165+) adds weight to the application. | Not required, but strong GRE quantitative (162+) or overall GMAT or GMAT Focus (at least 80th percentile) scores add weight to the application. |
| Key features | Almost all modules involves dealing with real-world financial data (from sources such as Bloomberg terminals, Refinitiv, etc.) | Outstanding coverage of CFA topics (95% of CFA Level 1 and 80% of CFA level 2). |
| Target jobs | Graduates will typically place 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: 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), or even Financial Engineer (e.g., in an investment bank to design structured products). | Graduates will typically place in a financial company, but will also have opportunities at finance departments of non-financial companies. In both cases, roles are likely to be more of a generalist nature with less intense data exposure. Typical examples will be Financial Analyst or corporate analyst at commercial or investment banks, but graduates will also have ample opportunities at mutual funds, hedge funds, and other financial firms. |
| Affiliations | UCL, through this programme, is a University Partner for the CQF Institute, which provides networking opportunities and career resources for those pursuing a career in quantitative finance. | UCL, through this programme, is a CFA® affiliated university, entitling students to apply for scholarships to reduce exam and registration fees. |
Tuition fees and scholarships
Tuition Fees
The 2025-26 fees will be £47,100 for UK and Overseas students. Learn more about tuition fees.
Scholarships and Funding
Careers
As data disrupts and drives organisations, now more than ever employers are looking for finance specialists with high levels of data science literacy. The MSc Finance with Data Science programme provides you with the skills required to be a finance specialist, equipped 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 taught at UCL School of Management’s home in Canary Wharf, the heart of London’s dynamic financial centre. This strategic location gives you opportunities to build a network within the financial industry, including with UCL School of Management alumni, whilst you study with the careers team organising and facilitating talks from industry leaders from around the Wharf.
You will have access to a Corporate Speaker Series with leading industry experts, providing insights into current market topics and personal reflections on pursuing careers in finance, as well as alumni networking events to help new graduates navigate their next steps.
The programme aims to provide individuals with the knowledge, understanding and skills to engage with specialist roles in the modern global financial industry. These roles can 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), or even Financial Engineer (e.g., in an investment bank to design structured products).
Contact
For further information regarding the MSc Finance with Data Science, please contact the Postgraduate Team.
For further queries regarding admissions please see the UCL Postgraduate Admissions Webpage.
Other programmes of interest
UCL and the UCL School of Management offer a range of finance and data science-related programmes, while this programme is unique in combining the two, please note other programmes that may be of interest to you.
Programmes delivered by the UCL School of Management
Programmes delivered by UCL's Computer Science department
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FAQs
You may apply now for a place on a programme without a current English test as long as you send your qualification as soon as you receive it. If you are offered a place, it will be conditional on you providing evidence of meeting UCL's English Language Requirements before the start of the programme.