Job Description

Lesaka Technologies, within the Consumer Division, is looking for a

Fraud Risk Management: Data Analyst

to support the identification, assessment, and mitigation of fraud, AML, and operational risks across the organisation. The role applies data analytics, technical tools, and risk-based methodologies to detect anomalous behaviour, support investigations, assess control effectiveness, and drive remediation initiatives that strengthen preventative and detective controls.

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Key Responsibilities

Data Analysis

Perform in-depth data analysis to identify fraud risks, operational anomalies, and control weaknesses. Collect, integrate, and analyse data from multiple sources, including transaction systems, customer databases, and external data feeds. Clean, validate, and preprocess data to ensure accuracy and reliability. Assess data quality and integrity to support investigations and regulatory reporting.

Risk & Remediation

Apply an understanding of the fraud and operational risk lifecycle from detection to closure. Conduct root cause analysis on fraud incidents, operational failures, and control breaches. Develop and manage remediation plans, including actions, owners, timelines, and success measures. Track remediation progress and ensure timely closure of risk issues.

Investigation & Reporting

Support fraud investigations with data-driven insights and evidentiary analysis. Analyse transactional and behavioural data to identify suspicious activity and emerging trends. Prepare clear, concise reports and dashboards for senior management, risk, and compliance stakeholders. Ensure reporting meets governance and regulatory standards.

Monitoring & Surveillance

Design and maintain monitoring and surveillance processes to detect suspicious activity and control breaches. Support near real-time monitoring capabilities. Review and prioritise alerts from fraud detection systems based on risk severity. Recommend improvements to alert logic, thresholds, and escalation processes.

Risk Assessment & Mitigation

Develop and apply risk scoring methodologies. Conduct risk assessments across products, processes, and systems. Recommend and implement control and process improvements. Maintain the Fraud Risk Register and track remediation actions.

Dashboards & Automation

Design and maintain Power BI dashboards providing insight into fraud risks, investigations, and remediation progress. Develop and maintain SharePoint lists and workflow automation (e.g. Power Automate). Ensure dashboard accuracy, performance, and usability.

Continuous Improvement

Identify emerging fraud trends and operational vulnerabilities. Enhance fraud detection models and analytical approaches. Stay informed on industry best practices and regulatory developments.
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Stakeholder Engagement

Work closely with Compliance, IT, Operations, and Business teams. Engage with regulators, law enforcement, and external industry partners as required.
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Qualifications & Experience

BCom in Information and Technology Management Risk Management (Fraud, Operational, or Enterprise Risk) Data Analytics, Data Science, or Data Visualisation Informatics or Information Systems Business or Applied Analytics Project Management (qualification or proven delivery experience)

Experience

1-2 years' data analysis experience in fraud, risk, operations, or financial services. Experience working with large datasets to identify anomalies and trends. Exposure to fraud risk, operational risk, compliance, or control environments. Experience supporting remediation, audits, or issue management processes.
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Technical Skills

SQL proficiency (BigQuery or similar preferred). Experience with Power BI, Looker, Tableau, or similar tools. Strong understanding of data quality, lineage, and system dependencies. Ability to validate data used for risk and regulatory reporting.
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Behaviours

Strong ownership and accountability. Ability to manage multiple priorities simultaneously. Comfortable working in fast-paced, evolving environments. * Strong communication skills across technical and non-technical stakeholders.