Design, develop, and maintain advanced detection rules and automated response mechanisms to surface insider and fraud risk
Deep-dive into user, system, and financial data to uncover complex fraud tactics and potential abuse by insiders or privileged users
Identify and mitigate the risk of issues such as account misuse, privilege escalation, and social engineering within the organization
Collaborate with fraud analysts, KYC operations, compliance, and the broader security team to improve high-risk workflows
Create, maintain, and operationalize detection logic for insider and fraud scenarios
Share domain best practices in threat modeling and detection with the engineering team.
Requirements
Bachelor’s degree in Computer Science, Information Security, or relevant field
7+ years of hands-on experience in security engineering or detection engineering, with a strong focus on insider threat or fraud risk
Direct experience building, tuning, and operating detection and monitoring solutions (e.g., SIEM, EDR, DLP, user behavior analytics, and fraud detection platforms)
Expertise designing and implementing DLP controls and correlating exfiltration techniques with insider scenarios
Working knowledge of modern cloud-native architectures and how they impact identity, access, and monitoring
Experience with coordinating incident response and digital forensics.
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