Sr. Fraud Analyst

Wave Accounting is hiring a Sr. Fraud Analyst for a remote role open to applicants in Canada. It pays CAD 70k-CAD 106k a year and Level rates it ; you can apply on Wave Accounting.

Level's read on this job

Little AI ●○○○ is how Level rates this role: aI is not part of the work.
The posting lists this role as remote.
Tools and skills the posting cites include Gemini.
Level classifies it as a senior role.
Level lists 7 other open roles at Wave Accounting.

AI in this role

Gemini

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 careers@waveapps.com. 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.

How we rate this

Sr. Fraud Analyst at Wave Accounting rates 30 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.