Sas Fraud Management Admin

Description:

SAS Fraud Management Application Administrator to oversee the administration, maintenance, and optimization of the SAS Fraud Management (SFM) platform.
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Key Responsibilities
• Arabic speakers with transferrable iqama preferred.
• Install, configure, and administer SAS Fraud Management (SFM) application and related SAS components.
• Ensure the availability, performance, and security of SAS SFM across production, test, and development environments.
• Manage user access control, roles, and security configurations in compliance with regulatory requirements.
• Monitor SAS SFM system performance, ensuring real-time fraud detection capabilities remain operational.
• Investigate and troubleshoot application issues, working closely with IT, fraud risk teams, and SAS support.
• Manage system upgrades, patches, and hotfixes while minimizing downtime.
• Support the fraud strategy team in deploying, testing, and optimizing fraud detection rules and models.
• Collaborate with data analysts to fine-tune fraud detection algorithms for better accuracy and efficiency.
• Assist in implementing fraud detection workflows and case management enhancements.
Certifications
• SAS certification (e.g., SAS Certified Platform Administrator, SAS Certified Fraud Management Specialist) is preferred.
Technical Skills & Experience
• 3+ years of experience in SAS Fraud Management (SFM) administration or SAS application support.
• Strong knowledge of SAS Platform Architecture, Linux/Unix environments, and SQL databases.
• Experience with SAS Viya, SAS Base, SAS Macro, and scripting languages (Shell, Python, or PowerShell).
• Familiarity with real-time fraud detection systems, machine learning models, and data analytics tools.
• Strong understanding of fraud risk management, transaction monitoring, and case management workflows.
• Experience in system integration (APIs, MQ, Kafka, or web services) is a plus.
Preferred Experience
• Previous experience in banking, financial services, or fintech fraud operations.
• Hands-on experience with fraud detection rules, AI/ML models, and behavioral analytics.