Fraud Prevention Specialist - Analytics and Identity - CIAM

AIR CANADA; Dorval; Vor Ort; CAD 110.000 - 140.000; Vollzeit

Zusammenfassung

Air Canada is seeking a Fraud Prevention Specialist – Analytics and Identity (CIAM) to protect revenues, loyalty, and customer accounts by turning complex data into detection mechanisms, automation, and reporting.

You will build SQL data models in Snowflake, apply anomaly detection, design automations with Python and Power Automate, and create Power BI dashboards while collaborating with IT, Loyalty, Payments, and Legal teams.

Qualifikationen

• Bachelor’s degree in computer science, engineering, information systems, mathematics, or related quantitative field (or equivalent).
• At least five years of experience in fraud prevention, risk management, or data analysis.
• Advanced proficiency in SQL and experience modeling large, messy datasets in Snowflake or similar.
• Proven ability to automate and report using Python, Power Automate, PowerShell, Power BI, and advanced Excel.
• Solid knowledge of customer identity and account security: registration, login, MFA, SSO, profile and consent data.
• Ability to solve problems autonomously and adapt to evolving fraud risks.
• Excellent communication skills to convey technical findings to non-technical stakeholders.
• Demonstrated punctuality and reliability in a fast-paced environment.

Aufgaben

• Data Foundations: Create, optimize, and maintain complex queries in SQL and reusable data models in Snowflake for large datasets from multiple sources.
• Fraud Analysis: Apply anomaly detection, segmentation, network analysis, and behavioral profiling to spot fraud rings and assess incidents.
• Automation: Design and execute automations and data workflows (Power Automate, Python, PowerShell) to replace manual detection and reporting.
• Reporting: Create dashboards and reports in Power BI and Excel, communicating findings to stakeholders and leadership.
• Identity Expertise: Serve as the CIAM expert on customer identity ecosystems and how they impact fraud risk.
• Identity Initiatives: Own fraud and risk requirements for identity initiatives and validate solutions with QA and UAT.
• Account Security: Support measures to secure customer accounts and mitigate credential stuffing, bots, and enumeration attacks.
• Payments and Partners: Bridge payment data with identity signals and assess risks with loyalty and payment partners.
• Rules and Strategy: Measure detection rule performance and adjust based on data-driven insights.
• AI Threats and Tools: Monitor AI-facilitated threats and use AI tools to accelerate analysis, ensuring outputs are validated.
• Stakeholders and Vendors: Coordinate with multiple teams and manage vendor relations for investigations and roadmaps.
• Roadmap: Contribute to fraud/identity roadmap, ROI cases, and RFx evaluations.
• Privacy: Handle data per privacy requirements and maintain reproducible detection logic.

Kenntnisse

SQL

Snowflake

Python

Power Automate

Power BI

Advanced Excel

CIAM knowledge

Fraud analytics

Data modeling

Ausbildung

Bachelor’s degree in CS/Eng/Math

Tools

Snowflake

KQL

REST API

OAuth

Jobbeschreibung

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 new 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, and advanced Excel functions, including practical use of AI tools to accelerate work.
• Solid practical knowledge of customer identity and account security: registration and login journeys, authentication, multi‑factor authentication, single sign‑on, profile and consent data, and the flow of identity data between systems.
• Ability to solve problems autonomously, draw defensible conclusions from poorly documented data and systems, and anticipate evolving fraud and identity risks.
• Excellent communication skills to explain technical findings to a non‑technical audience, manage multiple initiatives, and handle confidential information with discretion.
• Demonstrated punctuality and reliability to support the overall success of the team in a fast‑paced environment.

Important Assets

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

Assets

• Knowledge of KQL or another log query language and knowledge of privacy and consent laws and regulations such as PIPEDA, GDPR, or CASL.
• Professional certification, such as a CFE designation, or a recognized AI/machine learning, data, or identity management certification.

Conditions of Employment

Candidates must be eligible to work in the country concerned at the time an offer of employment is presented and are responsible for obtaining necessary work permits, visas, or other authorizations. Proof of eligibility must be provided before the start date.

Language Requirements

All things being equal, 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 workplace that showcases the unique contribution of our employees to our business success.

As an equal opportunity employer, we encourage diverse applications so that we can build a workforce that is varied and representative of our customers and the communities where we live and offer our services.

Air Canada thanks all applicants for their interest, but only those selected for an interview will be contacted.