System Data Analytics Specialist (Fraud / Callsign Optimization)

Proven experience working directly with Callsign (configuration, tuning, or analytics) 5+ years of experience in fraud prevention, risk analytics, or authentication systems in the banking sector Strong SQL, Python, and data visualization skills (e.g., Power BI, Tableau) Familiarity with behavioral biometrics, device fingerprinting, and event-based fraud modeling Excellent analytical mindset and ability to interpret complex data flows Strong communication skills in English (Arabic is a plus) Experience with machine learning models used for fraud or risk scoring (preferred) Exposure to other fraud platforms (e.g., ThreatMetrix, Feedzai, SAS Fraud Management) (preferred) Knowledge of regulatory environments in MENA banking and SAMA compliance standards (preferred)

Calibrate and fine-tune Callsign fraud detection and authentication engine Analyze data models, risk signals, and rule outputs Work on continuous improvement of Callsign workflows, journeys, and intervention logic Conduct deep analytics on fraud event data, behavioral biometrics, and system logs Build dashboards, performance metrics, and reporting pipelines Configure system integrations between Callsign and core banking systems, APIs, or orchestration layers Support the deployment of new fraud scenarios and machine learning models Manage test environments, perform regression testing, and validate production changes Liaise with fraud strategy, IT security, and vendor teams Document configurations, model changes, and system updates Provide expert guidance on Callsign data structures, risk scoring, and orchestration capabilities