Financial Data Analytics (Master's program)
Overview
The Master of Financial Data Analytics (MFDA) aims to train highly qualified finance professionals with the computational skills essential for success in today's ever-changing financial markets.
Aimed at working professionals, this unique graduate program trains students in both finance and related data analytic skills and is suitable for business graduates with or without an advanced mathematics background. Applicants to the MFDA can be from a variety of educational backgrounds, from business, economics and finance, to mathematics, computer science, information technology and other quantitative areas.
There is an immense amount of data created every day, and the financial industry has benefited the most from data analytics. Banking and financial markets use information and analytics in creating a competitive advantage for their organizations. The need for professionals who can combine their finance and market expertise while supporting these emerging technologies is growing. Graduates of the MFDA will be trained in how to analyze financial data with data analytic skills including AI programming and applications.
The MFDA program includes eight courses and a choice of internship or project. The courses cover finance and data analytics skills applied to finance. It is a two-year full-time in-person program but can be accelerated to one year.
The MFDA is a GARP Academic Partner; the program curriculum equips students with the required knowledge to approach the Part I Exam of the Financial Risk Manager (FRM) professional certification. Recognized in every major global market, the FRM is the leading certification for Risk Managers
International students may be eligible for a .
Admissions
In addition to the , MFDA applicants must meet the following program-specific requirements:
- While applicants may hold any four-year undergraduate degree (or its 3-year equivalent from a recognized institution in countries where it is the accepted practice), preference is given to applicants whose undergraduate degree is in the field of business, economics, finance, information technology, computer science, modelling and computer science, engineering, mathematics, statistics, physics, actuarial science, or other quantitative fields.
- While not required, GMAT/GRE/CFA Level 1 may be recommended to strengthen your application or in lieu of GPA requirement.
- A statistics course is required. Linear algebra and calculus are highly recommended.
- If applicable, a minimum score of 7 on the IELTS or 100 on the TOEFL. (Note that these English language proficiency scores are slightly higher than those required for some other graduate programs.) Visit the of this calendar for additional details.
- There may be an interview for applicants prior to admission.
Please see for specific dates. Note that the application deadlines listed are for both the online application and all supporting documentation.
Applications for admission to all graduate studies programs are submitted online. There are five steps you must go through to complete the application process. See for step-by-step instructions.
Many of our graduate programs are extremely competitive; the number of qualified applicants normally exceeds the number of seats available for each intake. Satisfaction of minimum entry requirements does not ensure admission.
Additional information
Program courses:
- Financial Management
- Investment
- Financial Econometrics
- Financial Derivatives Securities
- Financial Risk Management
- Business Analytics
- Programming and Data Processing
- Artificial Intelligence Programming
Applicants to professional or course-based programs are not normally considered for internal funding sources such as entrance scholarships, minimum funding packages, teaching assistantships, research assistantships or graduate research assistantships.
While external scholarships and awards for graduate students who fall under the above criteria are often limited, we encourage you to explore some of the external available for possible funding opportunities.
Tuition fees for graduate programs are charged on a flat-fee or fee-per-credit basis and vary by program and student status.
For current, specific fees and details on flat-fee versus fee-per-credit programs, please see .
Contact the program:
Faculty of Business and Information Technology
905.721.8668 ext. 2830
fbit@ontariotechu.ca
Contact the School of Graduate and Postdoctoral Studies:
905.721.8668 ext. 6209
gradstudies@ontariotechu.ca
