Belonging to Air Canada is belonging to a Canadian icon, Air Canada recently voted best airline in North America. Take your career to new heights by joining our innovative and diverse team at the cutting edge of passenger air transport. The Fraud Prevention Specialist – Analytics and Identity (CIAM) is the anti-fraud team's expert in customer identity and account security, ensuring the protection of Air Canada's revenues, loyalty program, and customer accounts. This role transforms large volumes of complex and often incomplete data into detection mechanisms, automation, and reporting to combat account takeover, credential abuse, loyalty and payment fraud, and emerging AI-facilitated schemes, while minimizing customer friction. As the fraud and risk owner for customer identity initiatives, this role defines requirements and validates solutions delivered by technical teams and vendors.

Responsibilities

Data Foundations:

Create, optimize, and maintain complex queries in SQL and reusable data models in Snowflake for large datasets from multiple sources that are often incomplete or inconsistent, ensuring identity signals underlying fraud detection are captured and reliable.

Fraud Analysis:

Apply anomaly detection, segmentation, network analysis, and behavioral profiling techniques to spot fraud rings and emerging schemes, and quickly perform impact assessments and root cause analyses during ongoing incidents.

Automation:

Design, build, and execute automations and data workflows (Power Automate, Python, PowerShell, scheduled tasks) that replace manual detection, case triage, bulk account processing, and periodic reporting activities.

Reporting:

Create dashboards and reports in Power BI and Excel,



and communicate findings and control performance to stakeholders and senior management in audience-appropriate language.

Identity Expertise:

Act as the Cyber Fraud team's go-to expert regarding the customer identity ecosystem (registration and login, multi-factor authentication, passwordless access, single sign-on and federation, sessions, profile and consent data) and how this ecosystem creates or mitigates fraud risk.

Identity Initiatives:

Own fraud and risk requirements for identity initiatives, platform changes, and profile migrations, and validate solutions delivered by technical teams and vendors through user acceptance testing, quality assurance activities, and data integrity checks.

Account Security:

Support measures to secure customer accounts, including mass account locking, mandatory credential resets, and profile remediation, and help mitigate credential stuffing, bot, and enumeration attacks.

Payments and Partners:

Bridge payment and transaction data with account and identity signals to support payment fraud prevention, and evaluate identity and data-sharing risks presented by loyalty partners, commercial partners, and payment partners, including during current partner onboarding.

Rules and Strategy:

Measure the performance of fraud detection rules, false positives and false negatives, and customer friction, and recommend data-driven adjustments.





AI Threats and Tools:

Monitor AI-facilitated threats (synthetic identities, deepfakes and voice cloning, automated account creation, and agentic bots) and recommend controls; use AI tools to accelerate analysis, validating all outputs before they are used for decision-making.

Stakeholders and Vendors:

Collaborate with Digital Solutions, IT Security, Loyalty, Payments, Contact Centers, and Legal and Privacy teams to align controls with business objectives, and manage vendors regarding investigations, escalations, anomalies, roadmaps, and service levels.

Roadmap:

Maintain a forward-looking vision of fraud and identity enhancements and contribute to the roadmap, business cases, and evaluation of RFPs and RFQs in collaboration with Strategic Sourcing.

Privacy:

Handle customer, payment, and identity data in accordance with privacy and consent requirements, and maintain documentation, guides, and detection logic so work can be reproduced.

Qualifications Mandatory

Bachelor’s degree in computer science, engineering, information systems, mathematics, or a related quantitative field (or equivalent work experience).

At least five years of experience in fraud prevention, risk management, or data analysis, including hands‑on experience with schemes such as account takeover, credential abuse, bots, and loyalty or payment fraud.

Advanced proficiency in SQL and proven experience modeling large, messy datasets from multiple sources in Snowflake or a comparable cloud data platform.

Proven ability to build automation and reporting using Python (or an equivalent tool), Power Automate, PowerShell, Power BI,

📌 Fraud Prevention Specialist (Dorval)
🏢 Air Canada
📍 Dorval