Associate, e-KYC Data Analyst

NEW

Kuala Lumpur, Malaysia

Permanent

Duties & Responsibilities

Data Analysis & Insights: Perform detailed analysis of data related to eKYC results, AML/CFT operations, and customer onboarding to ensure compliance with regulatory requirements and internal policies. Identify trends, anomalies, and actionable insights by analyzing large datasets. Develop and maintain dashboards, reports, and visualizations to support decision-making processes across teams. Data Quality & Accuracy: Validate and verify the accuracy of data used for analysis to ensure reliability and compliance with industry standards. Conduct regular data cleansing and preprocessing to improve data quality and usability. Collaboration & Communication: Collaborate with Compliance, Technology, and other Operations teams to support the enhancement of eKYC systems, workflows, and reporting mechanisms. Present findings, insights, and recommendations to stakeholders across various departments in a clear and concise manner. Data Systems & Process Improvement: Work with technical teams to optimize data pipelines and ensure efficient data retrieval and storage. Provide support in developing and implementing automation solutions to streamline repetitive data-related tasks. Regulatory & Industry Alignment: Stay updated with industry trends, regulatory changes, and best practices related to data analytics in the eKYC/AML/CFT domain. Support the organization in aligning data-related processes with regulatory requirements and internal standards. Reporting & Documentation: Generate periodic and ad-hoc reports summarizing key findings, insights, and metrics for management review. Maintain proper documentation of data analysis processes, methodologies, and workflows. Reporting & Documentation:Support any ad-hoc assignments or projects as assigned by the supervisor.

Requirements

Key Skills and Competencies:
Strong analytical skills with the ability to work with large datasets. Proficiency in data analysis tools such as SQL, Python, R, or other relevant programming languages. Experience with data visualization tools (e.g., Tableau, Power BI, or similar). Strong understanding of data management principles and practices, including ETL processes and data quality frameworks. Excellent problem-solving skills and attention to detail. Strong communication and presentation skills to effectively share insights and recommendations.