MSc Financial Technology with Data Science
Bristol, United Kingdom
DURATION
1 up to 2 Years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
25 Jul 2025*
EARLIEST START DATE
Sep 2025
TUITION FEES
GBP 35,500 / per year **
STUDY FORMAT
On-Campus
* home applicants deadline: 8 August 2025
** overseas full-time tuition
Introduction
From crowdfunding to cryptocurrencies, and from automated trading to Alipay, recent innovations in financial technologies have revolutionised the way we spend, save, borrow, and invest. Companies in the financial services sector are now able to intelligently harness data to provide tailored products and services; big technology corporations offer financial services to customers through their social media accounts; and disruptive technology startups have quickly scaled to challenge the dominance of traditional banks by developing new forms of finance from the ground up.
This MSc offers an opportunity to join the financial technology revolution. You will learn the key design features of a number of financial technology applications and will develop skills to implement, assess and engineer these technologies. You will also develop an understanding of the computational, statistical and machine learning principles necessary for insightful large-scale data analysis used in data-driven finance.
Hosted by a world-leading engineering faculty, this is a technology-focused MSc and not a finance or accounting programme that is traditionally provided by a business school. Therefore, we expect applicants to have a strong background in computer science, engineering or a numerate science. A background in economics or finance is not expected or required.
This MSc is likely to appeal to applicants looking to start or advance their careers in data-driven finance and technology. The UK is a world leader in financial technology and the Bristol region has a flourishing fintech ecosystem. The programme has been co-designed with industrial partners and will offer opportunities to engage with industry on real-world commercial projects
Gallery
Admissions
Postgraduate Online Events
from 25th November 2024- 4th of December 2025
Curriculum
On entry, you will take one of two foundational units, depending on your previous experience. Students without software development experience will take a unit in Software Development, Programming and Algorithms; alternatively, students with software development experience will take a unit in Statistical Computing and Empirical Methods. When you arrive, your unit choice will be decided, based on your previous experience, in consultation with your personal tutor.
The remainder of the programme consists of compulsory units such as Large-Scale Data Engineering; Introduction to Financial Technology; Introduction to AI and Data Analytics; Advanced Financial Technology; and Financial Technology Group Project.
All students will complete their studies with an individual research or implementation project of their choosing from a selection proposed by project supervisors. This unit will provide students with first-hand experience in planning, running, documenting, and presenting a substantial piece of original work in the field of financial technology. The aim of this unit is to give students a substantial opportunity to integrate material from all taught units that they have studied as part of the programme, to demonstrate the breadth and depth of their learning on the MSc.
Unit names
- Large-Scale Data Engineering for Financial Technology
- Introduction to Financial Technology
- Advanced Financial Technology
- Financial Technology Group Project
- Introduction to AI and Data Analytics
- Financial Technology Individual Project
Select 20 credit points from:
- Software Development: Programming and Algorithms for Financial Technology
- Statistical Computing and Empirical Methods for Financial Technology
Program Tuition Fee
Career Opportunities
This programme has been co-designed with industrial partners to ensure that graduates are equipped with highly in-demand analytical, statistical and programming skills suitable for a range of technology careers in the financial services sector, as well as data scientist and data engineer roles in other non-finance industries. Graduates will also be prepared for careers in research and development or could go on to launch a fintech startup.
Program Admission Requirements
Show your commitment and readiness for Grad school by taking the GRE - the most broadly accepted exam for graduate programs internationally.