Finance - Financial Data Science

Fintech (the merging of finance, data and technology) is transforming financial services. New and emerging technologies such as big data analytics, blockchain, machine learning and AI, cloud computing and cryptocurrencies are transforming how business is conducted. This exciting masters will equip students for a career addressing global business needs for data science expertise particularly in the financial services industry.

Students will learn from some of the leading academic minds in this area as well as influential visiting speakers from the world of digital finance and technology. Our course blueprint covers the gamut of data research and analysis to practical programming and software development for financial services.

The MSc in Financial Data Science is suitable for graduates of engineering, computer science, mathematics, and business (with quantitative modules), with a talent for and interest in applying data science to problems particular to the realm of financial services.

Subjects taught

Fintech is transforming financial services leading to the emergence of challenger digital banks, innovative fintech start ups and new and emerging technology companies, driving employment demand in the financial sector. Students undertaking the MSc in Financial Data Science will be immersed in how financial markets operate and the ongoing FinTech revolution in this space. The programme features the theory and practice of cutting-edge quantitative analysis, optimisation, and machine learning and equips students with the market knowledge and financial data science skills to succeed in this new and emerging digital environment for banking and financial market transactions.

To achieve an MSc in Financial Data Science students complete 10 core modules over the Autumn and Spring Trimesters. In the Summer Trimester, students must complete Ethics in Financial Services and choose one of three pathways:

1. Green Data Science plus 2 option modules or
2. Green Data Science plus Summer Internship or
3. FinTech Incubator Project

Places on the summer modules will be made available for online registration in March.

Autumn Trimester
Core modules
Quantitative Methods for Finance
Capital Markets & Instruments
Derivative Securities
Financial Analysis
Financial Econometrics
Python for Financial Data Science

Spring Trimester
Core modules
Banking & Finance in the Digital Age
Portfolio & Risk Mgmt
Data Science for Trading & Risk Mgmt
Machine Learning for Finance

Summer Trimester
Core module
Ethics in Financial Services

Plus one Pathway
Pathway A
Green Data Science
plus 2 option modules:
Mergers and Acquisitions
Financial Technology
Structured Finance
Pathway B
Green Data Science
Summer Internship
Pathway C
FinTech Product Development Project

Please be advised that the above reflects the 2023/2024 curriculum structure and is subject to change each year. Option modules listed are indicative of what has been delivered in previous years and are also subject to change. Summer taught modules are delivered in blocks over one or two weeks.

Entry requirements

Please review the entry requirements below. The UCD Smurfit Admissions Office staff have expertise in reviewing international qualifications from around the world and will be able to assess your application's comparability to the Irish entry requirement.

Graduates with an undergraduate degree in Business, Finance or any degree with a significant quantitative element (such as engineering, physics or mathematics) are eligible to apply to this programme.

Applicants may be asked to undertake the GMAT or GRE at the Programme Director’s discretion.

Two completed academic reference forms from referees who can assess applicant's maturity, motivation
and intellectual ability. Part-time students can provide employer references.

Note: Note that graduates of UCD Lochlann Quinn School of Business are not required to submit the reference form

Application dates

Once you have collated the required documentation and reviewed the entry requirements for your programme of interest, you can now apply online.

You must apply online using our dedicated student information portal. You will be required to enter contact details, upload your documents and answer two essay questions (each approximately 300 words). We would ask that you seriously consider both essays and answer these in the context of the programme you are applying to. Try to not replicate your CV and demonstrate what makes you different from other applicants. There are no right or wrong ways to complete these essays.

Application Deadlines:
Applications are assessed on a rolling basis and courses will close once they are filled. We advise you to apply as early as possible to avoid disappointment. Please note certain scholarships may require you to apply before a certain date – please refer to our scholarship page online. If you have any questions in relation to deadlines or availability please email


12 months full-time, 24 months part-time.

Enrolment dates

Starting End August 2024

Post Course Info

Career Opportunities
The MSc in Financial Data Science is at the cutting edge of emerging digital technologies and data analysis in Finance. The programme provides an enviable array of career options upon graduation including:

Data science
Financial Services
Investment Management
Risk Management
Banking & Credit Risk

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Part time,Daytime,Full time

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