Fincrime BAU analyst

RESPONSIBILITIES: Manage knowledge and transition from the current teams into dedicated Financial Crime technology support teams, including SLA/OLA identification, Data Quality (DQ) analysis, and detailed activity level documentation. Enhance and maintain the data collation and reporting processes and applications to ensure accurate and timely availability of data for decision-making processes. Develop and enforce data governance policies and procedures to ensure data integrity, security, and compliance with regulatory requirements. Collaborate with various teams and functions to understand their data processes and needs, and provide guidance and support in establishing efficient data collection, storage, and retrieval processes. Monitor and analyze the performance of the current state processes to identify areas for improvement, implement upgrades, and troubleshoot any issues to minimize downtime. Conduct regular data audits to identify and resolve data quality issues, ensuring the accuracy and reliability of data used for reporting and analysis. Support end-users with current processes, providing guidance on data entry, extraction, and interpretation. Prepare and present reports and analyses to support strategic decision-making processes. SKILLS: 5-7 years of BAU/support management experience. Background in BAU management with KYC, Transaction Monitoring, and/or similar regulated processes. Understanding of E2E BAU lifecycle management for IT Application Services. Knowledge and experience in managing reporting applications and proficient in data management. Excellent problem-solving and troubleshooting skills to identify and resolve system issues. Excellent verbal and written communication skills to effectively interact with stakeholders at various levels. Strong analytical and critical thinking abilities to interpret complex data and provide insights. Ability to work collaboratively with cross-functional teams to understand their business needs and translate them into technology solutions. Detail-oriented with a focus on data accuracy and integrity.