
Forensic Data Analytics Specialist at CRDB Bank
MANAGER FORENSIC
Location
Tanzania Head Office
Department
DEPARTMENT OF RISK AND COMPLIANCE
The Forensic Data Analytics supports the bank’s internal investigations by analyzing transactional and operational data to detect and report potential fraud, misconduct, or regulatory breaches. This role is responsible for extracting and interpreting data from core systems to support forensic reviews and investigation, provide insight for corrective actions, and contribute to enhancing the bank’s internal control environment.
Principle Responsibilities
Data Analytics & Investigations
- Extract, clean, and analyze data from core banking, digital, and operational systems to identify irregularities or suspicious behaviour.
- Apply forensic techniques to detect fraud patterns, internal abuse, policy violations, or breaches of procedure.
- Assist in root cause analysis of identified anomalies, including reconstruction of timelines and user activity mapping.
Investigation Support & Documentation
- Prepare data-supported findings, exhibits, and reports for use in internal reviews, disciplinary actions, or regulatory compliance submissions.
- Ensure data integrity, confidentiality, and proper documentation standards are upheld throughout the investigation cycle.
- Maintain structured audit trails and case documentation.
Reporting & Visualization
- Develop investigation dashboards, visualizations, and reports using tools such as Power BI or Tableau.
- Translate technical analysis into simple, actionable insights for Forensic, Compliance, and Legal teams.
Qualifications Required
- Bachelor’s Degree in Data Science, Computer Science, Statistics, or a related field.
- Minimum 3 years of hands-on experience in data analysis, forensic audits, fraud analytics, or internal investigations, preferably within the banking or financial services sector.
- Proven ability to interpret complex datasets, including transactional logs, customer records, and system access logs.
- Strong SQL skills (mandatory).
- Proficiency in Excel and at least one data analysis language/tool: Python, R, or SAS.
- Experience with BI/reporting tools such as Power BI, Tableau, or QlikView.
- Familiarity with banking systems and financial data sources (e.g., core banking, e-channels, card systems).
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