Compliance Analytics and Insights Analyst

SCIENTE; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

SCIENTE is seeking a detail-oriented data analytics professional to support Anti-Financial Crime (AFC) data analytics, surveillance model validation, testing, and system enhancements in Singapore. The role emphasizes accuracy, regulatory compliance, and modernization initiatives including AI/ML-enabled capabilities.

Responsibilities include data analysis, SQL/Excel extraction, UAT, testing, dashboard QA, and cross-system AFC testing across Core Engine platforms, with comprehensive documentation

Qualifications

• Bachelor's degree in Data Science, Statistics, Finance, Business Administration, Computer Science, or related discipline
• Minimum of 5 years' experience in the financial services industry
• Hands-on experience with AML systems, transaction monitoring, and Anti-Financial Crime compliance
• Experience in User Acceptance Testing (UAT), system testing, and defect management
• Experience in data analytics, reporting, and project support or coordination
• Proficiency in Microsoft Excel and SQL
• Experience with data visualization tools such as Power BI or Qlik
• Strong analytical and critical thinking skills

Responsibilities

• Conduct data analysis to identify patterns, trends, anomalies, and potential risks related to money laundering, fraud, and sanctions
• Perform data extraction, validation, and analysis using SQL, Excel, or other analytics tools
• Support data analytics activities, including alert performance reviews, anomaly identification, and quality assurance of dashboards and reports
• Support monitoring and validation of AFC surveillance models and Core Engine systems, ensuring data accuracy and performance tracking
• Support multi-system AML testing across Core Engine platforms, primarily through User Acceptance Testing (UAT)
• Document testing results, defects, and analytical findings in accordance with established standards and procedures
• Support project delivery activities across testing, implementation, and post-go-live issue management
• Coordinate with business users, technology teams, and project stakeholders to ensure timely resolution of system issues

Skills

AML systems

Transaction monitoring

UAT testing

Data analytics

Excel

SQL

Power BI

Qlik

Analytical thinking

Education

Bachelor's degree in Data Science, Statistics, Finance, Business Administration, Computer Science, or related discipline

Tools

Power BI

Qlik

Job description

We are seeking a detail-oriented and analytical professional to support Anti-Financial Crime (AFC) data analytics, surveillance model validation, testing, and system enhancements.

This role plays an important part in ensuring the accuracy, efficiency, and regulatory compliance of AFC monitoring systems while supporting modernization initiatives, including AI/ML-enabled capabilities.

Mandatory Skill-set

• Bachelor's degree in Data Science, Statistics, Finance, Business Administration, Computer Science, or a related discipline;
• Minimum of 5 years' experience in the financial services industry;
• Hands-on experience with AML systems, transaction monitoring, and Anti-Financial Crime compliance;
• Experience in User Acceptance Testing (UAT), system testing, and defect management;
• Experience in data analytics, reporting, and project support or coordination
• Proficiency in Microsoft Excel and SQL;
• Experience with data visualization tools such as Power BI or Qlik;
• Strong analytical and critical thinking skills;

Desired Skill-set

• Practical knowledge of automation technologies (e.g., Robotic Process Automation (RPA);
• Familiarity with AI/ML applications in compliance or financial crime detection.

Responsibilities

• Conduct data analysis to identify patterns, trends, anomalies, and potential risks related to money laundering, fraud, and sanctions;
• Perform data extraction, validation, and analysis using SQL, Excel, or other analytics tools;
• Support data analytics activities, including alert performance reviews, anomaly identification, and quality assurance of dashboards and reports;
• Support monitoring and validation of AFC surveillance models and Core Engine systems, ensuring data accuracy and performance tracking;
• Support multi-system AML testing across Core Engine platforms, primarily through User Acceptance Testing (UAT);
• Document testing results, defects, and analytical findings in accordance with established standards and procedures;
• Support project delivery activities across testing, implementation, and post-go-live issue management;
• Coordinate with business users, technology teams, and project stakeholders to ensure timely resolution of system issues;

Confidentiality is assured, and only shortlisted candidates will be notified for interviews.