Director, Fraud Data and Analytics

Requisition ID: 264919

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

The Team

The Global Fraud Technology team develops and manages enterprise fraud capabilities that protect Scotiabank, its customers, and its employees across all channels and products. The Fraud Data & Analytics organization is responsible for the data, analytics, intelligence, and AI foundations that power fraud detection, fraud response, scam prevention, investigations, and risk management capabilities across the Bank.

We partner closely with Fraud Operations, Fraud Strategy, Data Science, Risk Management, AML, Payments, Digital Banking, Enterprise Data Office, and Enterprise Technology teams to deliver trusted, scalable, and governed fraud data capabilities that support real-time decisioning, advanced analytics, machine learning, regulatory reporting, and operational insights.

The Role

The Director, Global Fraud Technology – Fraud Data & Analytics is accountable for the strategy, delivery, governance, and operation of the Bank’s fraud data and analytics ecosystem. This role leads teams responsible for fraud data platforms, feature engineering, data products, fraud intelligence capabilities, reporting and visualization platforms, model enablement services, and AI-driven analytical solutions.

The Director is responsible for ensuring fraud data is trusted, accessible, timely, secure, and governed while enabling advanced analytical capabilities that improve fraud detection effectiveness, customer protection, operational efficiency, and business decision-making.

The role works closely with business and technology leaders to define the future-state fraud data strategy and drive enterprise-wide adoption of modern data and AI capabilities.

Key Accountabilities

Strategy & Leadership

Develop and execute the multi-year fraud data and analytics strategy aligned with enterprise fraud, risk, and technology objectives.
Define the target-state fraud data architecture and operating model supporting realtime and batch analytical workloads.
Establish strategic roadmaps for fraud data platforms, data products, AI enablement capabilities, and analytical services.
Partner with senior business and technology stakeholders to prioritize investments and define long-term analytical capabilities.
Drive innovation through the adoption of modern data platforms, advanced analytics, AI, and machine learning technologies.
Lead strategic vendor and technology partner relationships supporting fraud data and analytics capabilities.

Fraud Data Platform Ownership

Own the fraud data ecosystem supporting fraud detection, fraud response, investigations, scam prevention, and fraud intelligence functions.
Establish scalable and resilient data platforms supporting high-volume transactional and behavioral data processing.
Drive modernization initiatives involving cloud-native data architectures, streaming platforms, data lakes, and analytical environments.
Ensure seamless integration of internal and external fraud data sources across the enterprise.
Deliver high-quality, trusted, and governed fraud data assets for operational and analytical consumption.

Data Products & Feature Engineering

Lead development and management of enterprise fraud data products and reusable analytical assets.
Establish feature engineering capabilities supporting fraud detection models, AI solutions, and advanced analytics initiatives.
Build and maintain fraud-specific feature stores and analytical datasets.
Drive standardization, reuse, and scalability across fraud data assets.
Partner with business stakeholders to define and prioritize strategic data products.

Analytics & Fraud Intelligence

Deliver enterprise fraud intelligence capabilities that provide actionable insights into fraud trends, emerging threats, scam typologies, and customer risk.
Enable advanced analytical capabilities including network analytics, graph intelligence, behavioral profiling, anomaly detection, and predictive analytics.
Partner with Fraud Strategy and Fraud Operations teams to identify opportunities for fraud loss reduction and operational optimization.
Establish enterprise reporting and visualization capabilities supporting executive, operational, and regulatory reporting needs.
Drive analytical innovation through the application of AI and emerging technologies.

AI & Model Enablement

Provide technology platforms and services supporting fraud data science and machine learning teams.
Enable the full model lifecycle including development, deployment, monitoring, explainability, performance measurement, and governance.
Support deployment of AI-driven fraud capabilities across detection, response, and intelligence functions.
Establish MLOps and analytical operations capabilities that improve model reliability and scalability.
Partner with Model Risk Management and Validation teams to support governance requirements.

Data Governance & Risk Management

Establish and maintain data governance frameworks supporting fraud data assets.
Ensure compliance with regulatory requirements, privacy obligations, data retention standards, and information security policies.
Define and monitor data quality standards, controls, lineage, and stewardship practices.
Partner with Enterprise Data Office and Risk Management teams to strengthen fraud data governance and accountability.
Ensure appropriate controls exist around analytical models, reporting, and data usage.

Operational Excellence

Establish performance metrics, service-level objectives, and operational controls across fraud data platforms.
Drive continuous improvements in data quality, availability, timeliness, and operational efficiency.
Ensure platform resiliency, disaster recovery readiness, and operational support processes meet enterprise standards.
Manage portfolio budgets, vendor relationships, and strategic investments.
Deliver measurable business outcomes through improved data accessi