Data Science Simon Fraser University

Overview

The Data Science B.Sc. at Simon Fraser University provides students with a robust interdisciplinary foundation in modern analytical techniques. By integrating knowledge from diverse fields, the programme prepares graduates to navigate complex data landscapes and implement effective technological solutions in various professional environments.

This curriculum is uniquely designed to bridge the gap between theoretical mathematics and practical business applications. Students develop a versatile toolkit that allows them to interpret large datasets and translate findings into actionable insights for industry leaders. The programme emphasises the development of critical thinking and technical proficiency to address real-world challenges.

Why Data Science at Simon Fraser University?

This programme stands out due to its interdisciplinary nature, drawing expertise from the Department of Statistics and Actuarial Science alongside the Faculty of Science. Students benefit from a collaborative learning environment that spans multiple disciplines, including Computing Science and Business. Additionally, the programme offers the flexibility to begin studies at the Surrey campus, providing access to modern facilities and a focused academic community.

Tuition Fee Breakdown

• International fee: CAD 37442 per year
• National fee: CAD 7502 per year

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum combines rigorous quantitative training with practical computing skills. Modules may include:

• Statistics
• Computing Science
• Mathematics
• Business
• Analytical Methods
• Technological Solutions

Careers with Data Science

Graduates are well-prepared for a wide range of career possibilities across business and industry sectors. The focus on evidence-based decision-making and analytical problem-solving makes alumni highly competitive for roles that require data interpretation and strategic planning. Potential career paths involve applying data-driven methodologies to improve organisational efficiency and drive innovation in technology-led fields.