Manager – AML Compliance, Transaction Monitoring

This is a fully remote position, open to applicants in Pakistan.

📋 Description

• Carry out daily operations within the TM Data Quality Management Framework for the AML TM system/product.

• Conduct regular data quality assessments using automated data quality dashboards and various processes.

• Establish, uphold, and periodically review data quality validation rules for Critical Data Elements (CDEs) related to the Transaction Monitoring system/process.

• Analyze reconciliation dashboards or processes and exception reports to ensure that TM system data is sufficient and free from data discrepancies.

• Collaborate closely with Compliance Data & Analytics and Data Governance teams on data management tasks.

• Maintain records of data quality controls.

• Supervise transaction monitoring system performance by tracking alert/case volumes and investigation results; provide coaching, direction, and training.

• Oversee data management by verifying ETL exception reports and processes, data mappings, and data quality reports.

• Collaborate with the Regulatory Technology team on AML Transaction Monitoring initiatives.

• Convert business, compliance, and regulatory requirements into structured Business Requirement Documents.

• Create technical specifications, perform User Acceptance Testing, and document analysis findings.

• Conduct typology coverage assessments and address any AML coverage deficiencies; resolve logic and configuration challenges in monitoring scenarios.

• Partner with users to develop initiatives that enhance and modernize transaction monitoring capabilities and services.

• Evaluate current and future surveillance, platforms, policies, and procedures to foster continuous improvement.

• Assist Internal Audit, model validation, and regulatory reviews related to data quality controls and Transaction Monitoring system operations.

• Provide Compliance with actionable financial crime risk intelligence through ad hoc extractions, analyses, and interpretations using SQL/relevant tools and statistical techniques.

• Serve as a subject matter expert, supporting colleagues in international locations on data quality issues.

• Develop tactical and scalable technology solutions for operational teams managing ad hoc compliance tasks and risks.

• Support proactive solutions for detecting AML risks and facilitating dynamic client monitoring using both internal and external data.

• Collaborate with AML investigators to establish data- and intelligence-driven investigation processes.

• Ensure adequate record-keeping, management information, and documentation related to AML.

• Aid in data integrity, data governance, and profiling activities.

• Complete special projects as assigned.

⛳️ Requirements

• Bachelor's/Master's degree in Engineering, Mathematics, Statistics, or a related field with strong quantitative and qualitative methodological skills.

• Knowledge of AML laws and regulations, along with a comprehensive understanding of AML and associated risks.

• Subject Matter Expert in AML Transaction Monitoring across various business lines like Retail/Corporate Banking, Correspondent Banking, and Trade.

• Significant hands-on experience in AML Transaction Monitoring models with relevant expertise in tuning and optimizing AML models.

• Proficiency in statistical inference (e.g., predictive analytics, clustering, Machine Learning Algorithms) and Python programming modules such as pandas, sklearn, pyspark, and numpy.

• Experience in Data Quality evaluations and related data cleansing techniques.

• Exceptional collaboration and team-building skills, demonstrating a commitment to working as part of a high-performing team of financial intelligence specialists.

• Strong verbal and written communication skills, along with experience in defending research findings.

• Familiarity with Data Management Frameworks such as Data Governance, Data Lineage, Data Catalog, and Data Quality.

• Additional knowledge of SAS-AML applications/SAS EG/SAS VIYA platforms.

• Experience in Consumer Financial Products/Payments/FinTech is advantageous; expertise in machine learning, statistical modeling, or data mining is a plus.

• Understanding of the data analysis pipeline, data infrastructure, big data, and ability to work effectively with large datasets.

• Experience with Risk Coverage Assessment, Model Validation, and Tuning.

• Certification from CAMS or equivalent is preferred.

🏝️ Benefits

• Remote work (RW)