Posted 10 days ago

Sr. Fraud Analyst

CanadaRemoteFull-time

AI Summary

The Senior Fraud Analyst identifies fraud patterns, evaluates controls, and improves prevention and detection strategies across digital customer and payment experiences by analyzing account activity, transaction behavior, and model outputs.

About this role

At Wave, we help small businesses to thrive so the heart of our communities beats stronger. We work in an environment buzzing with creative energy and inspiration. No matter where you are or how you get the job done, you have what you need to be successful and connected. The mark of true success at Wave is the ability to be bold, learn quickly and share your knowledge generously.

The Senior Analyst, Fraud Prevention & Detection is a hands-on fraud risk professional responsible for identifying fraud patterns, evaluating controls, and improving prevention and detection strategies across digital customer and payment experiences. This role analyzes account activity, transaction behavior, payment flows, model outputs, case trends, and other risk signals to identify emerging threats and recommend practical control improvements.

The Senior Analyst partners with Product, Engineering, Data Science, Compliance, Customer Care, and Operations to improve rules, scoring, decisioning, alerting, vendor tools, automation, and real-time detection capabilities. This role is accountable for delivering clear analysis, actionable recommendations, and measurable improvements in fraud outcomes, including reduced fraud losses, stronger fraud capture, lower false positives, reduced manual review volume, improved operational efficiency, and balanced customer experience. The ideal candidate brings strong fraud expertise, analytical rigor, urgency, and the ability to turn ambiguous fraud signals into clear actions that strengthen the business.

Here's how you will make an impact:

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 based on measurable results

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 and improve real-time detection capabilities

Support the fraud capability roadmap by identifying opportunities to improve rules, scoring, AI/ML model performance, identity verification, behavioral signals, vendor tooling, automation, and workflows

Prepare clear analysis, recommendations, business cases, and executive-ready summaries that explain fraud risks, tradeoffs, expected impact, and required actions

Support testing, launch, monitoring, and optimization of new fraud tools, vendor capabilities, detection strategies, and process improvements

Maintain SOPs, reporting routines, control documentation, and governance artifacts that support consistent fraud prevention and detection execution

You Thrive Here By Possessing the Following:

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 to identify fraud risks and recommend actions

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

Skills

AI/ML Model MonitoringAlertingControl DocumentationDashboardsDecisioning WorkflowsExcelFraud Rules DesignFraud ToolsOperational Data AnalysisReal-time DetectionRisk ScoringRoot Cause AnalysisRules EnginesSQLVendor Platforms

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