Cyber Operations Analyst

About the role

We are seeking a Cyber Operations Analyst to join our fraud team within the fintech division. The role provides continuous 24/7 monitoring of the Flash payment system and critical infrastructure, detecting and escalating threats, system anomalies, and fraudulent activity in real time to protect the organisation and its customers.

Key responsibilities

• Monitor Flash system dashboards, alerts, and transaction queues across rotational shifts to identify critical anomalies.
• Investigate and triage alerts, distinguishing genuine incidents from false positives and taking appropriate action.
• Escalate confirmed fraud cases and critical system events to the team lead and relevant stakeholders promptly.
• Log all incidents, actions taken, and outcomes in the case management system with accuracy and within required timeframes.
• Analyse historical incident data to identify emerging fraud typologies, cyber‑threat patterns, and system vulnerabilities.
• Conduct structured shift handovers, communicating open items, outstanding alerts, and critical context.
• Adhere to monitoring protocols, compliance requirements, and standard operating procedures.
• Report recurring alert patterns or system behaviours that may indicate emerging fraud trends or risks.
• Participate in team briefings, training sessions, and process‑improvement initiatives.

Required profile

• A diploma or degree in Information Technology, Computer Science, Finance, Cybersecurity, Data Science or a related field.
• Certifications in fraud prevention, cybersecurity or IT service management are advantageous.
• 1‑3 years of experience in operations, monitoring, fraud analytics or IT support.
• Experience in a financial services or payments environment is a plus.

Required skills

• Log analysis and interpretation of security event data.
• Endpoint telemetry and network traffic analysis.
• Proficiency with Microsoft Excel and Outlook.
• Basic understanding of payments systems and transaction flows (e.g., EFT, card schemes).
• Familiarity with fraud detection concepts such as transaction anomaly scoring and rule‑based flagging.
• Knowledge of network protocols, system architecture and common attack vectors.
• Experience with cloud monitoring environments.
• Awareness of AML (Anti‑Money Laundering) principles.