Director, FSI Predictive Technology

Responsibilities

• Lead the technical strategy, architecture, and roadmap for fraud technology built to scale and support customers in building, customizing, and operating fraud detection, prevention, investigation, and decisioning systems.
• Design reusable detection approaches that combine rules, machine learning, anomaly detection, behavioral analytics, graph analytics, entity resolution, and risk scoring.
• Partner with Data Science, ML Engineering, Product, and Customer Engineering teams to develop, evaluate, deploy, and continuously improve fraud detection capabilities for customer use cases.
• Identify, prioritize, and integrate fraud signals across transactional, identity, account, device, network, application, behavioral, and operational data.
• Establish frameworks for rapidly translating newly discovered fraud patterns into production rules, signals, models, and detection workflows that can be adopted across customer environments.
• Define and monitor detection effectiveness using metrics such as precision, recall, false-positive rates, detection coverage, alert quality, latency, and business impact.
• Lead technical root-cause analysis when fraudulent activity bypasses existing controls and drive improvements to detection logic, data coverage, and system resilience.
• Build reusable detection infrastructure, services, APIs, reference architectures, and frameworks that support multiple products, fraud types, customer environments, and business use cases.
• Evaluate emerging technologies and determine where AI, machine learning, graph analytics, automation, and analyst-assist tooling can improve fraud detection and response.
• Lead technical build and architecture reviews, driving alignment across Development, Data Science, Security, Risk, Product, Customer Engineering, and Service Delivery collaborators.

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