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Position Purpose:
We are seeking a Cybersecurity Senior Fraud Analyst to support our Identity Fraud Prevention Team, focusing on AI-driven fraud detection, deepfake mitigation, and advanced fraud penetration tactics. The ideal candidate will work closely with staff analysts to identify, analyze, and combat sophisticated fraud schemes leveraging Generative AI (GenAI), synthetic identities, and adversarial machine learning attacks. This role requires deep expertise in fraud detection methodologies, cybersecurity frameworks, and automation-driven fraud prevention strategies.
Key Responsibilities:
Fraud Analysis & Investigation:
Conduct in-depth analysis of identity fraud patterns, including synthetic identity fraud, credential stuffing, account takeovers (ATO), and deepfake-enabled fraud.
Develop AI-powered fraud detection models and continuously refine existing fraud prevention techniques.
Identify adversarial AI threats, including automated bot fraud, GenAI-enabled phishing, and social engineering attacks.
AI & Deepfake Detection:
Research and implement machine learning models to detect deepfake-generated identities, voice fraud, and AI-assisted fraud schemes.
Stay ahead of fraudster tactics using generative AI tools to fabricate convincing yet fraudulent documents, images, and videos.
Collaborate with security engineers and data scientists to develop countermeasures for deepfake-based fraud attempts.
Threat Intelligence & Red Teaming:
Perform advanced fraud penetration testing against identity verification and fraud prevention systems.
Assess vulnerabilities in biometric authentication, document verification, and AI-driven fraud defenses.
Monitor and analyze dark web and underground fraud forums for emerging identity fraud trends and tactics.
Collaboration & Incident Response:
Work closely with staff analysts, cybersecurity teams, and fraud risk managers to escalate fraud cases and implement risk mitigation strategies.
Assist in fraud investigations by providing AI-driven insights and real-time threat intelligence.
Partner with engineering and data teams to improve fraud detection algorithms and automation frameworks.
Continuous Improvement & Strategy:
Contribute to the development of next-gen identity fraud prevention frameworks.
Stay updated on NIST 800-63, AI risk mitigation best practices, and emerging fraud countermeasures.
Advocate for ethical AI use in fraud detection and ensure compliance with regulatory and industry standards.
Qualifications & Experience:
Required:
3-5 years of experience in fraud detection, cybersecurity, or AI-driven fraud prevention.
Strong understanding of identity verification, fraud analytics, and adversarial AI.
Hands-on experience with fraud detection tools, machine learning models, and automation frameworks.
Proficiency in Python, SQL, or other scripting languages for fraud analysis and data investigation.
Knowledge of deepfake detection techniques, AI risk mitigation, and biometric security.
Familiarity with fraudster TTPs (Tactics, Techniques, and Procedures) in digital identity fraud and organized retail crime.
Experience with fraud modeling, anomaly detection, and AI-driven threat intelligence tools.
Preferred:
Certifications such as CFE (Certified Fraud Examiner), CEH (Certified Ethical Hacker), or CISSP.
Experience working in CIAM, IAM, or identity fraud prevention environments.
Background in threat hunting, adversarial AI research, or fraud penetration testing.
Understanding of Generative AI ethics, deepfake countermeasures, and secure AI development principles.
Key Responsibilities:
Direct Manager/Direct Reports:
Travel Requirements:
Physical Requirements:
Working Conditions:
Minimum Qualifications:
Minimum Education:
Minimum Years of Work Experience:
Competencies:
For California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents:

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