Specialist Fraud Prevention - Analytics and Identity - CIAM

Air Canada; Dorval; On-site; CAD 95,000 - 130,000; Full time

Job summary

Air Canada, based in Dorval near Montreal, is seeking a Specialist in Fraud Prevention - Analytics & Identity (CIAM) to lead identity security initiatives and data-driven fraud detection across loyalty, payments and accounts.

You'll design and optimize SQL queries in Snowflake, build automations with Python and Power Automate, develop dashboards in Power BI, and partner with IT Security and Loyalty to balance risk with customer experience.

Qualifications

• Degree in CS/Engineering/IS/Math or equivalent.
• 5+ years in fraud prevention, risk or data analytics.
• Advanced SQL with large, multi-source datasets (Snowflake).
• Proven ability to build automations and reporting (Python, Power Automate, Power BI).
• Knowledge of customer identity and security: MFA, SSO, profiles.
• Strong communication and problem-solving skills.

Responsibilities

• Develop and optimize identity signals used for fraud detection.
• Apply anomaly detection and profiling to expose fraud patterns.
• Design automations and data flows to streamline detection and reporting.
• Build dashboards and communicate findings to stakeholders.
• Collaborate with IT Security, Loyalty and Payments on risk controls.

Skills

Advanced SQL

Fraud analytics

Python

Power Automate

PowerShell

Power BI

Data modeling

Communication

Problem solving

CIAM / Identity awareness

Education

Bachelor's degree in CS/Engineering/IS/Math or related field

Tools

Snowflake

SQL

Excel

Job description

Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation.
The Specialist, Fraud Prevention - Analytics & Identity (CIAM) is the fraud team's subject-matter expert on customer identity and account security, protecting Air Canada's revenue, loyalty currency and customer accounts. The incumbent turns large, complex and often incomplete data into detection, automations and reporting that address account takeover, credential abuse, loyalty and payment fraud, and emerging AI-enabled schemes, while minimizing customer friction. As the fraud and risk owner for customer identity initiatives, the incumbent defines requirements and validates the solutions delivered by technical teams and vendors.

Responsibilities

• Data foundations: Build, optimize and maintain complex SQL queries and reusable data models in Snowflake across large, multi-source datasets that are often incomplete or inconsistent, and ensure the identity signals fraud detection relies on are captured and reliable.
• Fraud analytics: Apply anomaly detection, segmentation, network analysis and behavioural profiling to expose fraud rings and emerging schemes, and provide rapid impact assessments and root-cause analysis during active incidents.
• Automation: Design, build and run automations and dataflows (Power Automate, Python, PowerShell, scheduled jobs) that replace manual detection, case triage, bulk account actions and recurring reporting.
• Reporting: Build dashboards and reporting in Power BI and Excel, and communicate findings and control performance to stakeholders and senior leadership in language suited to the audience.
• Identity expertise: Act as the fraud team's go-to expert on the customer identity ecosystem (registration and login, MFA, passwordless, SSO and federation, sessions, profile and consent data) and how it creates or closes fraud risk.
• Identity initiatives: Own the fraud and risk requirements for identity initiatives, platform changes and profile migrations, and validate what technical teams and vendors deliver through UAT, QA and data-integrity checks.
• Account security: Support actions to secure customer accounts, including bulk lockdowns, forced credential resets and profile remediation, and help mitigate credential stuffing, bot and enumeration attacks.
• Payments & partners: Link payment and transaction data with account and identity signals to support payment fraud prevention, and assess the identity and data-sharing risk of loyalty, commercial and payment partners, including new onboardings.
• Rules & strategy: Measure fraud rule performance, false positives/negatives and customer friction, and recommend data-driven tuning.
• AI threats & tools: Monitor AI-enabled threats (synthetic identities, deepfakes and voice cloning, automated account creation, agentic bots) and recommend controls; use AI tooling to accelerate analysis, validating all outputs before they inform decisions.
• Stakeholders & vendors: Work with Digital, IT Security, Loyalty, Payments, Contact Centre and Legal/Privacy to align controls with business goals, and manage vendors on investigations, escalations, defects, roadmaps and service levels.
• Roadmap: Maintain a forward view of fraud and identity enhancements and contribute to the roadmap, business cases and RFP/RFQ evaluations with Strategic Procurement.
• Privacy & documentation: Handle customer, payment and identity data in line with privacy and consent requirements, and keep documentation, runbooks and detection logic current so the work is repeatable.

Qualifications

Required

• Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics or a related quantitative field, or equivalent experience.
• Minimum 5 years of experience in fraud prevention, risk or data analytics, including hands-on work with patterns such as account takeover, credential abuse, bots and loyalty or payment fraud.
• Advanced SQL, with proven experience modelling large, messy, multi-source datasets in Snowflake or a comparable cloud data platform.
• Proven ability to build automations and reporting with Python (or equivalent), Power Automate, PowerShell, Power BI and advanced Excel, including practical use of AI tools to accelerate the work.
• Solid working knowledge of customer identity and account security: registration and login journeys, authentication, MFA, SSO, profile and consent data, and how identity data moves between systems.
• Self-directed problem-solver who reaches defensible conclusions from poorly documented data and systems, and anticipates where fraud and identity risk is heading.
• Clear communicator who can explain technical findings to non-technical audiences, manage multiple initiatives and handle confidential information with discretion.
• Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.

Strongly Preferred

• Hands-on experience with an enterprise Customer Identity and Access Management (CIAM) platform and identity protocols (OAuth 2.0, OIDC, SAML, REST APIs).
• Experience in the airline industry or with a large-scale loyalty or frequent-flyer program.

Assets

• Exposure to KQL or another log query language, and familiarity with privacy and consent regulations such as PIPEDA, GDPR or CASL.
• Professional certification such as CFE, or a recognized AI/ML, data or identity certification.

Conditions Of Employment

Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment. Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest.

Linguistic Requirements

Based on equal qualifications, preference will be given to bilingual candidates.

Diversity and Inclusion

Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.

As an equal opportunity employer, we welcome applications from all to help us build a diverse workforce which reflects the diversity of our customers, and communities, in which we live and serve.

Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.