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Required Fraud Group Manager
Tel Aviv-Yafo, Gush Dan, Israel
We offer the industrys only platform that fuses customer identity and anti-fraud solutions – customer identity management, identity verification, and fraud prevention.
We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.
About the Role:
The Fraud Group Manager leads the professional organization responsible for the "Intelligence Core" of our fraud detection products. You manage three specialized teams-Fraud Data Science, Fraud Research, and Fraud Analytics-that implement the core logic our customers use to fight fraud.
In this role, you aren't just a strategist; you are a Production Owner. You are responsible for the health, observability, and continuous improvement of detection logic in live environments. You work in a high-impact triad with Product Management and Platform Engineering, serving as the bridge between deep technical expertise and the customers who rely on our product to protect their business.
What youll do:
Group Leadership & Customer Engagement
Direct Management: Lead and scale a multidisciplinary organization of Data Scientists, Researchers, and Analysts.
Customer Fronting: Act as the primary technical fraud authority for our customers. You will join high-stakes meetings with CISOs and Fraud Heads to explain our detection logic, address performance concerns, and align our roadmap with their evolving threat landscape.
Stakeholder Orchestration: Partner with Product Management to define the "what" and Platform Engineering to ensure the "how" (infrastructure) meets your group's logic requirements.
Production Ownership & Quality Systems
Detection Observability: Own the end-to-end monitoring and health of fraud detection in production. You ensure that we have the visibility to know if a model is degrading or a specific customers detection is underperforming.
On-Call for Performance: Serve as the escalation point for critical detection failures or sudden spikes in false positives/negatives, ensuring rapid mitigation for impacted customers.
Quality Assurance Framework: Create and maintain a robust quality system (CI/CD for fraud logic) to ensure smooth, ongoing updates to detection models and heuristics without disrupting customer environments.
Lifecycle Management: Oversee the continuous tuning and optimization of live detection logic based on real-world feedback loops.
Technical Execution
Hands-on Vetting: Maintain deep technical fluency. You must be able to review Python code, validate complex SQL queries, and interpret model performance metrics to ensure they meet our high standards.
Logic Governance: Define the schemas and standards for how detection logic is developed, ensuring that research insights are effectively operationalized by the Data Science team.