- About the Role
- We are seeking an experienced Analytics Analyst – Fraud & AML to support fraud detection, Anti-Money Laundering (AML) monitoring, transaction analytics, and fraud prevention initiatives within the financial services/payments environment.
- The ideal candidate will have hands-on experience with fraud and AML analytics, transaction monitoring, rule development, anomaly detection, and fraud monitoring platforms. Experience with DataVisor, Navera, or similar fraud/AML monitoring solutions is highly desirable.
- Key Responsibilities
- Configure, maintain, and optimize AML and fraud monitoring systems.
- Design, develop, test, and optimize fraud detection and AML monitoring rules.
- Analyze transaction data to identify fraud patterns, trends, anomalies, and emerging risks.
- Develop fraud pattern identification models and monitoring processes.
- Support DataVisor fraud monitoring design, configuration, and integration activities.
- Investigate suspicious transaction patterns and emerging fraud typologies.
- Develop analytical reports, dashboards, and management insights.
- Monitor fraud detection performance and recommend improvements to existing rules and controls.
- Collaborate with fraud, AML, data, technology, and business stakeholders.
- Translate analytical findings into actionable fraud prevention and risk management recommendations.
- Required Skills & Experience
- Hands-on experience in Fraud Analytics and/or AML Analytics.
- Experience developing and optimizing fraud/AML detection rules.
- Strong SQL skills and experience analyzing large transaction datasets.
- Experience with fraud monitoring, transaction monitoring, or AML systems.
- Experience with DataVisor, Navera, or similar fraud monitoring platforms.
- Strong analytical, problem-solving, and pattern-recognition skills.
- Experience developing reports, dashboards, and management-level insights.
- Understanding of fraud typologies, transaction monitoring, anomalies, and risk indicators.
- Nice to Have
- Experience with Power BI, Tableau, or similar BI tools.
- Experience with machine learning-based fraud detection.
- Experience in banking, financial services, fintech, payments, or credit card environments.
- Knowledge of AML transaction monitoring and suspicious activity detection.
- Experience working with large-scale transactional/payment datasets.
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Analytics Analyst
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