Bachelor's degree in Mathematics, Statistics, Computer Science, Information Management, Economics, Actuarial Science or another relevant quantitative field.
Four to six years' relevant experience in data analytics, forensic analytics, fraud monitoring or financial-crime investigation; financial-services, insurance or banking experience is preferred.
Certification in data analytics or forensic technology tools is required; CFE, CPA(K), CFA, CISSP or a relevant postgraduate qualification is an advantage.
Demonstrated experience in fraud-rule design, anomaly detection, evidence handling and data-protection requirements.
Advanced SQL and working proficiency in Python or R.
Forensic analytics, anomaly detection, statistical testing and link analysis.
Fraud-monitoring rule design, testing, tuning and governance.
Power BI, Tableau, Qlik Sense or equivalent visualisation tools.
CaseWare IDEA, Alteryx, Cellebrite or equivalent forensic tools.
Relational databases, ETL processes and ERP data.
Digital-evidence preservation, chain of custody, metadata and log analysis.
Fraud typologies, relevant legislation and evidence-based report writing.
Application deadline27 Oct 2026
GK
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