Financial Crime Systems Associate - Testing & AI/ML

ACE Money Transfer Limited; Punjab; Vor Ort; PKR 900.000 - 1.500.000; Vollzeit

Zusammenfassung

ACE Money Transfer Limited is seeking an Associate – Financial Crime Systems to support the delivery, testing, and enhancement of financial crime technology platforms. The role focuses on system validation, data analysis, and change delivery, working closely with Product, Development, and Operations teams.

The ideal candidate will have experience with enterprise systems, UAT, and data-driven platforms, plus exposure to rules-based and AI/ML-driven financial crime detection models.

Qualifikationen

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Finance, or related field.
• 2–3 years of experience in financial services technology, enterprise systems, or delivery/testing roles.
• Experience with UAT, data validation, and testing of financial systems.

Aufgaben

• Support financial crime systems including transaction monitoring, screening, and case management platforms.
• Participate in UAT, regression testing, and pre-production validation for system changes and releases.
• Validate business and functional requirements against system behavior and outcomes.
• Assist with testing of rules, thresholds, workflows, and alerting logic.
• Perform data validation and reconciliation to ensure accuracy of system inputs and outputs.
• Support testing and validation of AI/ML and analytical models, including scenario and threshold changes.
• Collaborate with Product, Development, and vendor teams to manage defects and delivery timelines.
• Maintain testing, release, and system documentation.

Kenntnisse

Problem-solving

Adaptability

Collaboration

Communication

Ausbildung

Bachelor's degree

Tools

JIRA

Confluence

Python

SQL

Excel

Jobbeschreibung

ACE Money Transfer Limited is seeking an Associate – Financial Crime Systems to support the delivery, testing, and enhancement of financial crime technology platforms. The role focuses on system validation, data analysis, and change delivery, working closely with Product, Development, and Operations teams.

The ideal candidate will have experience with enterprise systems, UAT, and data-driven platforms, plus exposure to rules-based and AI/ML-driven financial crime detection models.