Sr. Fraud Analyst
W
WaveFintech, Financial Services
CanadaFull-TimeSenior
Salary70,400 - 105,600 CAD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- SQLMicrosoft ExcelData analytics
Requirements
- 5+ years of experience in fraud prevention, fraud detection, fraud strategy, payments risk, digital identity, fintech, banking, e-commerce, tax, or financial services fraud programs.
- Hands-on experience designing, tuning, testing, and evaluating fraud rules, risk scoring strategies, detection logic, alerts, fraud controls, or automated decisioning workflows.
- Strong analytical capability using dashboards, Excel, SQL or data querying tools, model outputs, transaction trends, case analysis, and operational data.
- Experience monitoring and improving fraud performance metrics such as fraud losses, fraud capture, false positives, manual review volume, operational efficiency, and customer friction.
- Demonstrated ability to identify root causes, connect patterns across data sources, and translate complex fraud signals into specific control recommendations.
- Experience partnering with Product, Engineering, Data Science, Analytics, Compliance, Customer Care, and Operations to implement fraud control improvements.
- Working knowledge of fraud tools, vendor platforms, rules engines, risk scoring systems, alerting processes, workflow tools, or real-time decisioning environments.
- Practical understanding of AI/ML fraud model outputs, model performance monitoring, feature evaluation, or data-driven decisioning in an operational environment.
Responsibilities
- Analyze fraud trends, attack patterns, account behavior, transaction activity, payment flows, model outputs, and other risk signals to identify emerging threats and control gaps.
- Design, tune, test, and evaluate fraud rules, risk scoring strategies, detection logic, alerts, and decisioning controls to improve fraud prevention and detection outcomes.
- Monitor fraud performance metrics, including fraud losses, fraud capture, false positives, manual review volume, customer friction, and control effectiveness, and recommend improvements.
- Conduct root cause analysis on fraud events, escalations, anomalous activity, missed fraud, and control failures, translating findings into specific corrective actions.
- Partner with Product, Engineering, Data Science, Analytics, Compliance, Customer Care, and Operations to implement fraud control enhancements.
- Support the fraud capability roadmap by identifying opportunities to improve rules, scoring, AI/ML model performance, identity verification, and vendor tooling.
- Prepare clear analysis, recommendations, and executive-ready summaries that explain fraud risks, tradeoffs, and expected impact.
- Support testing, launch, and optimization of new fraud tools, vendor capabilities, and process improvements.
- Maintain SOPs, reporting routines, control documentation, and governance artifacts.
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