Fraud & AML Strategy Co-op, BS/MS Students
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Job Description
Co-op student engaged in fraud & AML strategy design with a leading AI-powered fraud platform. Collaborating with experts to analyze data and optimize detection strategies.
Responsibilities:
- Fraud & AML Rule Development
- Assist in designing, testing, and tuning fraud and AML detection rules across account origination, transactions, and suspicious activity monitoring
- Help maintain and document rule libraries with proper governance and performance tracking
- Analytics & Experimentation
- Analyze transaction data to identify trends, anomalies, and emerging fraud or AML typologies
- Support experiments and pilot initiatives to test new fraud signals or detection approaches
- Cross-Functional Collaboration
- Partner with Data Science teams to translate fraud patterns into model features
- Work with Fraud & AML Operations teams to review case outcomes and validate detection coverage
- Workflow & Process Support
- Assist in defining fraud and AML workflows, including alerts, queues, and escalation paths
- Help evaluate third-party fraud or AML data sources for enrichment opportunities
- Insights & Reporting
- Contribute to dashboards, reports, and presentations that summarize fraud trends and strategy performance
- Support strategy recommendations for internal stakeholders
Requirements:
- Currently enrolled in co-op program or recently completed a Bachelor’s or Master’s degree in:
- Computer Science, Data Science, Engineering, Economics, Business Analytics, Finance, or a related field
- Curious about fraud prevention, AML, risk management, and fintech
- Comfortable working with data and eager to learn industry tools and frameworks
- Able to think analytically and communicate findings clearly
- Canadian Citizen or PR of Canada
- Basic Qualifications
- Experience with or coursework in SQL (required)
- Familiarity with Python, data analysis, or statistics through coursework or projects
- Strong analytical and problem-solving skills
- Ability to work independently and collaboratively in a fast-paced environment
- Nice to Have (Not Required)
- Exposure to fraud, AML, payments, or financial services concepts
- Experience with dashboards or analytics tools (e.g., Tableau, Looker, Power BI)
- Understanding of rule-based systems, workflows, or case management concepts
Benefits:
- Hands-on experience in real-world fraud and AML strategy
- Exposure to AI-driven risk platforms used by global enterprises
- Mentorship from experienced fraud strategists and data scientists
- Practical experience that aligns well with careers in fintech, risk, analytics, or data science
- Hourly Rate, CAD20-25/hour
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