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Program Information

Program Information

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Program Information

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About the Program

Apply Now Admission Requirements

The Master of Data Analytics (MDA) program blends technical and professional skills to prepare you for a dynamic career in finance, tech innovation, insurance, health care and beyond. There are three streams of study to choose from: artificial intelligence; finance, banking, and insurance; and generalist.

  • Program name: Data Analytics
  • Degree level: Masters
  • Duration: 12 months (8 months coursework + 4 months co-op)
  • Application deadline: January 31 (International); June 15 (Domestic)
  • Contact: MDA_inquiry@uwo.ca
Course-based
Co-op
Technical Skill Training
Hands-on Learning
Speciality Fields

Program Structure

The fall term and winter term curriculum consists of set of seven “core” courses, and three “specialty field” course electives, plus Personal Career Development classes and activities.

Term 1

In the first term (September - December), students will take 4 core courses, such as:
  • Statistical Modelling I - MDA9159
  • Business Skills for Data Scientists - MDA9160
  • Databases I - CS9159
  • Introduction to Machine Learning - DATASCI9000
  • One specialty field elective course

Term 2

In the second term (January - April), students will complete their core courses, taking courses such as:
  • Statistical Modelling II - STATS9155
  • Data Analytics Consulting - MDA9144
  • Unstructured Data - CS9117
  • Generalist & Finance, Banking and Insurance Students - two specialty field elective courses
  • Artificial Intelligence students - Ethics in AI (required) plus one elective

Advanced Courses

If you have a significant background in a data analytics-related field, you will have the opportunity to deepen your knowledge in that discipline. Students with a strong background in core data analytics subjects can request to substitute a core course with a graduate-level data analytics course with MDA Program Director approval.

Artificial Intelligence

Artificial Intelligence (AI) is a specialty designed for students aiming to build careers in data analytics enriched by a deeper understanding of AI techniques and their practical applications. This field will equip you with in-demand skills by covering key topics such as neural networks, big data management and intelligent agents. Specializing in AI positions graduates competitively in the job market, especially in roles focused on automation, predictive modeling and intelligent systems.
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Finance, Banking and Insurance

Finance, Banking and Insurance is a specialty that emphasizes the strategic use of data analytics in financial services and risk management. You will gain expertise in financial modeling, investment portfolio analysis and survival analysis, preparing you to assess and manage financial risk in banking and insurance contexts. Specializing in this field positions graduates for impactful, data-driven roles in financial institutions and related sectors.
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Generalist

Generalist is a specialty designed for students seeking a broad and versatile foundation in data analytics, rather than focusing on a single domain. Deepen your expertise beyond the core curriculum by exploring advanced topics such as artificial intelligence, financial risk management and database systems. This flexible approach equips graduates with a diverse skill set applicable across multiple industries.
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Personal Career Development

Strengthen your professional skills with Personal Career Development classes and activities throughout the fall and winter terms. Through seminars, lectures, presentations, panel discussions and workshops, you will gain industry insight for a competitive advantage. Be prepared to enter the workforce with professionalism and confidence.

Networking

Networking opportunities with revelant industry partners will take place over the fall and winter terms. These events will help you to build your professional network, connect with potential employers and learn how to effectively position yourself to pursue a professional career in data science.

Industry Engagement

Throughout the academic terms, you will work on cases and with real clients on consulting projects. You will build skills to work in a business setting, solving problems as you learn to create meaningful impact.

Co-op Term

In the last term (May - August), students apply advanced data analytics knowledge in real-world settings, gaining valuable work experience and building professional networks. This hands-on approach helps bridge the gap between academic learning and industry expectations. 

Industries

MDA students are great fits for roles in any industry, and are particularly in demand in the Finance, Banking and Insurance; Corporate Enterprise; Energy/Utilities; Government;  Health Care; and Tech Innovation (AI/Machine Learning) fields.

Roles

Typical co-op positions include roles such as: Data Scientist, Big Data/Data Architect, Data Analyst, Business Analyst, Technical Analyst, Actuarial Analyst, Financial Analyst, Operations Analyst, Software Developer, Senior Consultant, Cloud Consultant, AI/ML Consultant, and Data Engineer.

Technical Skills

The MDA program will provide you with the skills needed to be proficient in technical data analytics and apply those skills in a specific field, or as a generalist practitioner.

Data Science and Machine Learning
  • Machine Learning
  • Artificial Intelligence
  • Statistical Modelling and Inference
  • Natural Language Processing
  • Exploratory Data Analysis
Data Handling and Engineering
  • Unstructured Data
  • Database Skills
  • Data Munging and Wrangling
  • Distributed Data Management and Analysis
  • SQL
Professional Skills
  • Ethical Data Analysis
  • Business Skills
  • Communication Skills
Programming and Tools
  • Power BI
  • Python
  • R
  • Visualization
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Real-World Work Experience

Experiential learning is a critical component of the MDA program. Building on the course-based portion of the program, the experiential learning term further allows you to apply advanced knowledge in data analytics in a "real world" environment while also developing a network of professional contacts. It is an outstanding opportunity to help you showcase your ability to perform in a professional environment and in a data-analytics role.

Previous Employers

MDA is proud to have a vast number of employers that return year after year to hire co-op students. Oftentimes, students will get hired on full-time after graduation.

Finance, Banking & Insurance

  • Intercontinental Exchange (ICE)
  • Canada Life
  • Royal Bank of Canada
  • Scotiabank
  • EY

Health Care

  • Trillium Health Partners
  • London Health Sciences Centre
  • The Hospital for Sick Children
  • Roche
  • SE Health

Technology

  • IBM
  • Messagepoint AI
  • Larus Technologies
  • Rogers
  • Bell Canada

Corporate Enterprise

  • Canadian Tire Corporation
  • Loblaws Companies of Canada
  • Mitsubishi
  • Recipe Unlimited Corporation
  • Purolator

Energy/Utilities

  • Hydro One
  • Bruce Power
  • Siemens Energy
  • Rystad Energy
  • Amarize (formerly LaFarge)

Government

  • Canada Revenue Agency
  • Health Canada
  • Agriculture and Agri-foods Canada
  • Statistics Canada
  • Bank of Canada

Apply to the MDA Program

Application Deadline:

International Students – January 30

Domestic Students – June 15

Apply Now Admission Requirements

After Graduation

MDA graduates have found tremendous success post-graduation, and many move quickly into leadership roles in industry, such as:

  • Senior Data Scientist
  • Senior Actuarial Insights Analyst
  • Engineering Lead
  • Senior Data Engineer
  • Finance Manager
  • Manager, Model Quality - Retail and Small Business
  • Manager, Exposure and Capital Analytics
  • Associate Director, Credit Risk Management
  • Director, Fraud Detection and Optimization

Our Graduates

Headshot of Krishang Karir

Krishang Karir

MDA '25

I felt stuck professionally and was looking for a change that would reignite my passion. The MDA program is more than just an academic credential; it’s a career accelerator. The combination of in-demand skills and the hands-on experience from my co-op directly led to a full-time offer before I even graduated. More importantly, there's a powerful support system behind the program that ensures everyone is given the opportunity to succeed.

Headshot of Yihan Sun

Yihan Sun

MDA '23

MDA is undoubtedly a great starting point for building a career in data, helping you turn data into impactful stories. This program sparked my curiosity to explore data infrastructure and fueled my passion for learning cutting-edge software and technologies. The co-op experience provided a solid foundation to launch my career, and ultimately led to a full-time position with my co-op employer.

Headshot of Bassam Ejaz Syed

Bassam Ejaz Syed

MDA '25

I specialized in Artificial Intelligence to focus on developing AI-driven solutions. I had the flexibility to shape my own path, choosing courses that strengthened my technical experience and analytical thinking, as well as building consulting and communication skills essential for applying data solutions in real-world business settings. The combination of coursework, hands-on projects, and the co-op experience opened doors to opportunities I wouldn’t have had otherwise.

Frequently Asked Questions

The MDA program is a one-year full-time, in-person program. It is not available to take part-time or online.
We only have one intake per year in September. This is because the program is structured so that some courses in the fall term are required for courses in the winter term.
Given the skills and knowledge gained during their time in the MDA program, graduates have accepted data-focused roles within a broad range of industries across a wide variety of functional areas of organizations. Past graduates have accepted positions in areas/departments such as Pension Analytics, Business Insight Analytics, Fraud Detection Analytics, Incentives Analysis, Credit Risk Measurement, Business Analytics, Data Engineering, Financial Analytics, Data Consulting, Artificial Intelligence and Machine Learning Research
The third term of the MDA program sees students actively apply for positions of interest and gain self-marketing skills in securing their experiential learning opportunity through either formal or informal recruiting activity. Recognizing the varied career goals & objectives of students, the MDA program does not ‘place’ students in pre-determined positions with a set of defined organizations. The program provides support to students in securing their individual experiential learning opportunity through personal career management classes & activities throughout the Fall & Winter terms, one-on-one coaching and advising with the program’s Career Services Officer and by promoting potential positions of interest via a program-specific electronic job board.