Fraud Analytics Data Analyst

Salmon Group Ltd; Philippines; On-site; PHP 600,000 - 1,000,000; Full time

Job summary

Salmon Bank (Rural Bank) Inc., the banking arm of Salmon Group Ltd., is building its fraud analytics capability in the Philippines. We are seeking a data analyst to join the Anti-Fraud team, focusing on credit and card fraud, using SQL and internal systems to uncover patterns.

As the first dedicated data analyst in this growing function, you will analyze diverse data sources, develop dashboards and reports, and collaborate across Risk, Product, Engineering, and Compliance to prevent fraud and

Qualifications

• Strong SQL skills and ability to work with large, complex datasets.
• Experience in data analysis, fraud analytics, risk analytics, or financial crime investigations.
• Genuine curiosity for data and persistence in analysis.

Responsibilities

• Conduct in-depth investigations of high-risk fraud alerts and complex cases using SQL and internal systems.
• Analyze transactional, customer, device, and behavioral data to identify fraud schemes and emerging patterns.
• Develop and maintain analytical reports, dashboards, and fraud performance metrics for management and operations.
• Identify new fraud typologies and recommend enhancements to detection rules and monitoring controls.
• Perform ad hoc data analysis to support fraud investigations and business requests.
• Collaborate with Fraud Operations, Risk, Product, Engineering, and Compliance teams to improve prevention processes.

Skills

SQL

Data analysis

Fraud analytics

Financial crime investigations

Job description

Salmon Bank (Rural Bank) Inc., the banking arm of Salmon Group Ltd., is building its fraud analytics capability in the Philippines. We are seeking a data analyst to join the Anti-Fraud team, focusing on credit and card fraud, using SQL and internal systems to uncover patterns.

As the first dedicated data analyst in this growing function, you will analyze diverse data sources, develop dashboards and reports, and collaborate across Risk, Product, Engineering, and Compliance to prevent fraud and