Fraud Strategy Intern: Analytics & Detection

Canadian Tire Bank; Welland; On-site; CAD 65,904,000 - 106,020,000; Full time

Benefits offered by this job

Competitive pay

Career growth opportunities

Product discounts

Broadband

Job summary

Canadian Tire Bank is seeking a student analyst to help detect and prevent fraud across the customer lifecycle. You will work with payment, account, and behavioral data to build and refine fraud detection strategies and respond to emerging trends.

The role emphasizes collaboration with Fraud Operations and other business units, using Python/SAS/R/SQL and Tableau to generate insights and support investigations. This is a hands-on learning opportunity in a dynamic financial services environment.

Qualifications

• Pursuing a post-secondary program in relevant fields.
• Strong analytical, mathematical, and problem-solving abilities.
• Programming experience in Python/SAS/R/SQL.
• Proficient in Microsoft Office (Excel, Word, PowerPoint).
• Familiar with Data Visualization tools like Tableau is a plus.

Responsibilities

• Use analytics to prevent and contain fraud across the customer lifecycle.
• Work with payment, account, and behavioral data.
• Develop fraud detection strategies across detection platforms.
• Monitor fraud detection rates and false positives against business goals.
• Collaborate with Fraud Operations and other business units.

Skills

Analytical thinking

Programming (Python/SAS/R/SQL)

Data visualization

Communication

Attention to detail

Team collaboration

Customer empathy

Technical foundation

Education

Currently enrolled in a post-secondary program (Math/Statistics/Economics/CS)

Tools

Python

SAS

R

SQL

Tableau

Job description

Canadian Tire Bank is seeking a student analyst to help detect and prevent fraud across the customer lifecycle. You will work with payment, account, and behavioral data to build and refine fraud detection strategies and respond to emerging trends.

The role emphasizes collaboration with Fraud Operations and other business units, using Python/SAS/R/SQL and Tableau to generate insights and support investigations. This is a hands-on learning opportunity in a dynamic financial services environment.