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A leading company in Singapore is seeking a Project Lead for AML and Trade Surveillance to manage compliance projects across regions. The ideal candidate will bring over 6 years of experience in Banking or IT, with expertise in data analysis and compliance systems. You will lead initiatives, collaborate with diverse teams, and ensure regulatory adherence while utilizing advanced data science techniques for risk management.
Key Responsibilities:
Lead and manage end-to-end AML and Trade Surveillance projects across regions, ensuring compliance with local and international regulatory requirements.
Provide techno-functional expertise in Compliance Reporting, including Information Barrier management, Preclearance, Personal Trading/Statements Review, Disclosure of Interests, and Employee Compliance monitoring.
Oversee AML Transaction Monitoring, KYC, Sanctions Screening, and Suspicious Activity Reporting (SAR) processes.
Collaborate with business and IT teams to implement robust surveillance models and data pipelines.
Perform detailed data analysis to support investigations, build machine learning models for risk classification, and generate actionable insights.
Utilize Data Science techniques for anomaly detection, risk scoring, and visualization of compliance metrics.
Engage stakeholders across business units and geographies to define requirements and implement scalable solutions.
Serve as a subject matter expert for internal audits, regulatory inquiries, and compliance risk assessments.
Required Qualifications & Skills:
6+ years of experience in Banking, Finance, or IT domains with a focus on AML and Trade Surveillance.
Bachelor of Science or similar related education background.
Certified CAMS (Certified Anti-Money Laundering Specialist) is mandatory.
Experience working across multi-cultural teams in international environments, particularly in APAC, UK, and US.
Strong knowledge of compliance systems and reporting platforms.
Hands-on experience with KYC tools, Sanctions Screening engines, and AML case management systems.
Proven ability to work with Data Science technologies, including:
o Python/R, Pandas, Scikit-learn, Matplotlib/Seaborn, etc.
o Experience with classification models, anomaly detection, and data visualization.
Strong communication skills and ability to lead client engagements.
Bachelor's/Master's degree in Computer Science, Data Science, Finance, or a related field.
Experience with Big Data platforms and cloud environments (AWS, GCP, Azure).
Familiarity with trade lifecycle and market surveillance systems.
Understanding of global regulatory frameworks (FATF, MAS, FCA, SEC, etc.).