Program overview
Admission Requirements
Intakes

Last updated on 2025-05-30

Program overview

Program Overview

The Bachelor of Science in Data Sciences and Analytics program is a unique collaboration between the Faculty of Mathematics and Science and the Goodman School of Business. This program stands out as one of only two BSc programs in Canada that effectively combines financial analytics with computational data science. It aims to bridge the gap between computational data sciences and business analytics, producing graduates who possess a robust understanding of programming for big data, data infrastructures, and business intelligence.

 

Program Structure

The Bachelor of Science in Data Sciences and Analytics program is designed to provide students with a comprehensive education in both data science and financial analytics. The program offers the following features:

  • Program Length: Typically spans over four years.
  • Students can choose between two concentrations: Financial Analytics or Computational Data Sciences.
  • Options for Honours or Co-op are available, allowing students to gain practical experience.
  • Experiential learning opportunities are integrated into the curriculum.
  • International opportunities may also be available for students seeking global exposure.

 

Featured Experiences

  • Co-op opportunities that provide real-world experience in the field.
  • Experiential learning components that enhance practical skills.
  • International opportunities for students to broaden their horizons.
  • Specialization options in areas such as machine learning, artificial intelligence, and financial risk management.

 

Career Options

Graduates of the Bachelor of Science in Data Sciences and Analytics program can pursue a variety of career paths in Canada, including:

  • Data Scientist/Engineer: Responsible for analyzing and interpreting complex data to help organizations make informed decisions.
  • Big Data Solution Architect: Designs and implements big data solutions to manage and analyze large datasets.
  • Financial (Risk) Analyst: Evaluates financial data to assess risks and provide insights for investment decisions.
  • Data Analytics Consultant: Advises organizations on how to leverage data analytics for business improvement.
  • Predictive Analytics Modeller: Develops models to predict future trends based on historical data.

 

DISCLAIMER: The information above is subject to change. For the latest updates, please contact LOA Portal's advisors.

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