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The MSc Financial Data Science at the University of Surrey is a one-year full-time programme (with part-time options) based at the Guildford campus, close to London’s financial hub. It provides a comprehensive curriculum blending financial market fundamentals, financial modelling, and the application of artificial intelligence and data science to finance.
The programme focuses on the mathematical foundations of machine learning, asset pricing, risk management, and portfolio theory, delivering both theoretical knowledge and practical coding skills using Python and real-world financial data.
Course Overview:
Core:
Artificial Intelligence and Financial Informatics
Financial Markets and Derivative Pricing
Derivatives Markets
Principles of Data Science
Mathematics of Data Science
Data Driven Methods
Dissertation
Bayesian Inference for Data Sciences
Fundamentals of Blockchain
Advanced Quantitative Methods in Economics
Machine Learning Methods and Big Data
Mathematical Time Series
Research-Led Teaching: Delivered by faculty active in cutting-edge mathematics and finance research.
Hands-On Learning: Practical coding exercises, data preprocessing, machine learning, and financial modelling using Python.
Dissertation Project: Full-time summer research project applying data science to a finance topic.
Interactive Teaching: In-person lectures, seminars, tutorials, and lab sessions focused on real-world data and problems.
Industry Links: Supported by industrial advisers from London’s financial sector, enhancing practical relevance and employability.
Graduate Employment: 94% of mathematics postgraduates at Surrey progress to employment or further study (HESA 2024).
Industry Demand: Graduates are highly sought for roles in financial data science, quantitative analysis, and risk management across banking, fintech, asset management, and consultancy sectors.
Further Study: The MSc provides strong preparation for doctoral research or advanced professional qualifications in finance and data science.
Location Advantage: Proximity to London’s financial district fosters networking, internships, and career opportunities.
Entry Requirements: A minimum of a 2:2 in a relevant UK honours degree, or a recognised equivalent international qualification. Your qualification should demonstrate basic knowledge and understanding in calculus, linear algebra, probability, and statistics. Specifically, you are suited to this course if your qualification has a reasonable level of mathematical contents in subjects such as mathematics, finance, economics, business, science, engineering, or computing. You may also be considered for the course if you have other professional qualification or experience of equivalent standing.IELTS Academic: 6.5 overall with a 6.0 in writing and 5.5 in each other element.TOEFL: 88 overall with R20, L19, S22 and W19Scholarships availableYour personal details, academic qualifications (predicted works too), a personal statement, evidence of your English language skills (with relevant qualifications), a reference and employment history are required for applications.Part time studies availableTwo Intakes: September and FebruaryFinancial Data ScientistQuantitative AnalystRisk ManagerPortfolio AnalystBig Data EngineerAlgorithmic TraderFinancial AnalystMachine Learning SpecialistBusiness Intelligence AnalystData Engineer
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University of Surrey
