Analyzes fraud patterns, transaction activity, payment flows, model outputs, and risk signals to identify threats and control gaps. Designs and tunes fraud rules, scoring strategies, alerts, and decisioning controls; monitors fraud losses, capture rates, false positives, and operational metrics. Partners with Product, Engineering, Data Science, Compliance, and Operations to implement fraud improvements, evaluate tools, conduct root-cause analysis, and provide actionable recommendations and executive-ready reporting.
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
At Wave, we value diversity of perspective. Your unique experience enriches our organization. We welcome applicants from all backgrounds. Let’s talk about how you can thrive here!
Wave is committed to providing an inclusive and accessible candidate experience. If you require accommodations during the recruitment process, please let us know by emailing [email protected]. We will work with you to meet your needs.
We use Google Gemini, a secure AI assistant, during interviews for note-taking purposes only. Notes are kept confidential and are not shared outside the hiring process. This allows our interviewers to stay fully focused on you during the conversation.
This advertised posting is a current vacancy.
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The capital city of Canada and the nation's fourth-largest urban area, Ottawa has proven a rapidly growing global tech hub. With over 1,800 tech companies, many of which are leaders in their sectors, the city's tech talent now makes up more than 13 percent of its total workforce. This growth is driven not only by the big players like UL Solutions and Dropbox, but also by a thriving startup ecosystem, as new businesses emerge to follow in the footsteps of those that came before them.
