
Senior Data Analyst
- Bangsar South, Kuala Lumpur
- Tetap
- Sepenuh masa
- Design, develop, and maintain reports and dashboards related to fraud risk, suspicious activity, transaction monitoring, and regulatory compliance.
- Build and enhance Power BI dashboards to visualize key AML and fraud KPIs (e.g., alert volumes, false positives, escalation rates).
- Analyze large datasets (transactions, customer behavior, device data) to detect anomalies, trends, and fraud patterns.
- Support the development of predictive risk models (e.g., fraud scoring, anomaly detection) using Python, pandas, scikit-learn, etc.
- Write and optimize complex SQL queries for extracting and transforming data from multiple fraud/AML-related systems.
- Collaborate with compliance officers, fraud investigators, data scientists, and product teams to gather requirements and build tailored data solutions.
- Conduct data validation, cleansing, and reconciliation to ensure accuracy of fraud/AML reporting and alert generation.
- Work closely with engineering teams to define and document data models
- Identify areas of improvement in alerting logic, rules tuning, or case management workflows through deep-dive analysis
- Partner with data engineering teams to improve data availability, reliability, and performance for analytics use cases
- Experience in AML, fraud detection/prevention, financial crime investigations, or regulatory compliance within fintech, banking, or digital payments.
- Familiarity with AWS services commonly used in fraud and AML pipelines (e.g., S3, Lambda, Glue, Athena).
- Experience with cloud-based data platforms (AWS, GCP) for secure, scalable handling of sensitive transaction and customer data.
- Exposure to third-party fraud or AML platforms is a plus.
- Understanding of KYC, SARs, transaction monitoring, sanctions screening, or related AML regulations (e.g., BSA, FATF, OFAC).
- Bachelor’s degree in Data Science, Computer Science, Information Systems, or related field.
- Minimum 3 years of experience in data analysis and business intelligence.
- Strong proficiency in Power BI (DAX, Power Query) and data modeling.
- Proficient in Python for data manipulation and report generation.
- Experience with SQL for working with relational databases.
- Experience with Agile Tools (JIRA, Confluence, BitBucket, Github)
- Excellent problem-solving skills.
- Strong communication skills and ability to work cross-functionally.
- Experience in handling financial datasets is a strong advantage.
- Team player with a proactive and accountable work attitude.