Financial Analytics

Overview

The MSc Financial Analytics is the programme for you if you have an interest in financial markets or financial technology (FinTech) and enjoy working with data. It shows you how data science, analytics, statistics and programming tools are used in the real world for the analysis and modelling of financial and economic data.



The programme will equip students with cutting-edge quantitative and computational techniques utilised by industry leading firms. The course aims to bridge the gap between complex quantitative models and financial decision making and does so by equipping students with dual skillsets in both finance and data analysis.



It can lead to exciting careers in areas such as financial data science, trading, software development, portfolio management, consulting, data analytics, risk management, business analytics and academia.



Course Structure

This degree will equip you with the cutting-edge quantitative and computational techniques utilised by leading finance and FinTech firms.



It will prepare you for a career in quantitative finance, trading, portfolio management, data analytics or risk management. You’ll learn how data science, business analytics, programming and statistical tools are used in the real world for the analysis and modelling of complex financial data.

Year 1

Core Modules

Financial Modelling in Python (15 credits)

AI & Trading (15 credits)

Advanced Financial Data Analytics (15 credits)

Asset Pricing (15 credits)

Applied Research Project (60 credits)

Advanced Analytics & Machine Learning (15 credits)

Financial Data Analytics (15 credits)

Data Management (15 credits)

Dissertation- MSc Financial Analytics (60 credits)



Optional Modules

Corporate Finance (15 credits)

Financial Market Structure (15 credits)

Graduate

Normally a strong 2.2 Honours degree (with minimum of 55%) or equivalent qualification acceptable to the University in Finance, Mathematics, Economics or other relevant quantitative subject. Science and Engineering disciplines will be considered where there is a significant mathematical component. Performance in relevant modules must be of the required standard. Applicants with a 2.2 Honours degree (scoring below 55%) or equivalent qualification acceptable to the University and sufficient relevant experience will be considered on a case-by-case basis.

Applicants are advised to apply as early as possible and ideally no later than 15th August 2025 for courses which commence in late September. In the event that any programme receives a high number of applications, the University reserves the right to close the application portal prior to the deadline stated on course finder. Notifications to this effect will appear on the application portal against the programme application page.



Please note: international applicants will be required to pay a deposit to secure a place on this course.

1 year (Full Time)

Entry Year: 2025/26

Career Prospects

This programme will equip students with cutting-edge quantitative and computational techniques and strategies used by leading finance and financial technology (FinTech) firms. Today, all full-service finance and business consulting firms employ Financial Analytics professionals in their operations as do many boutique firms, such as asset managers and hedge funds. Furthermore, many IT software organisations are attracted to graduates from this programme due to their specialism at the interface between computing, data analytics and finance.



For further opportunities to enhance your studies and career prospects please see the school website.

https://www.qub.ac.uk/schools/queens-business-school/student-opportunities/