Finance - Financial Data Science

Overview
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 new masters will equip students for a career addressing global business needs for data science expertise particularly in the financial services industry.

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.

What are the benefits?

UCD College of Business has a significant number of academics who are leaders in the area of financial data science and digital technology and financial services.

Immerse yourself 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, data science and machine learning on real financial data sets.

Graduates will attain skills and understanding in software programming, databases and applications of machine learning in finance.

Options include a FinTech start-up incubator program in the Summer Trimester in partnership with Nova UCD, (which offers guidance and support in bringing start-up ideas to market).

Subjects taught

What will I learn?
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. UCD College of Business has a significant number of academics who are leaders in the area of financial data science and digital technology and financial services. Given this critical mass of academic expertise, a growing gap in the jobs market for professionals with excellent data and technological skills in a finance context it is opportune for us to launch a programme which will equip 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.

How will I benefit?
This is a new course at the cutting edge of emerging digital technologies and data analysis in Finance. The course will not only attract graduates from a number of different backgrounds but can also be tailored to a wide variety of academic and professional objectives, providing an enviable array of career options upon graduation. Students will benefit from practitioner inputs as well as international academic perspectives.

Curriculum
To achieve an MSc in Financial Data Science student's complete a series of core modules over Trimester 1 and Trimester 2. In Trimester 3 students can complete either the industry internship; a FinTech incubator project; or take 3 additional option modules.

Autumn Trimester
Quantitative Methods for Finance
Capital Markets & Instruments
Derivative Securities
Financial Analysis
Financial Econometrics
Financial Theory

Spring Trimester
Banking & Finance in the Digital Age
Programming for Financial Data Science
Financial Data Science
Machine Learning for Finance

Summer Trimester
Ethics in Financial Services

Students choose one of the Pathways below:

Pathway A:
Green Data Science
plus choose two modules from the list below
Mergers and Acquisitions
Financial Technology
Advanced Treasury Management
Aircraft Finance

OR
Pathway B:
Summer Internship

OR
Pathway C:
FinTech Incubator Project

Please be advised that option modules listed are indicative of what has been delivered in previous years. What is offered each academic year is subject to change. Summer taught modules are delivered in blocks over one or two weeks.

Note that on-campus teaching is delivered under prevailing public health guidelines. In the event of a required change to planned delivery, further information about alternative delivery methods (including online delivery) will be confirmed with prospective and incoming students.

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.

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

Duration

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

Post Course Info

Career Opportunities
Graduates of the MSc in Financial Data Science will find career opportunities in the following areas:

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

More details
  • Qualification letters

    MSc

  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Part time,Daytime

  • Apply to

    Course provider