Transaction Monitoring Engine Specialist (AI/ML)

• Model Development: Design and develop AI/ML models for transaction monitoring, focusing on anomaly detection and risk scoring.
• Data Analysis: Analyze large datasets to identify trends, patterns, and potential risks associated with financial transactions.
• System Optimization: Continuously improve the performance of monitoring systems by tuning models, refining algorithms, and integrating new data sources.
• Regulatory Compliance: Ensure that transaction monitoring processes meet all regulatory requirements and industry standards, including AML/KYC.
• Collaboration: Work closely with cross-functional teams, including compliance, IT, and risk management, to align monitoring strategies with business objectives.
• Reporting and Documentation: Prepare detailed documentation of model development processes, performance metrics, and compliance efforts.
• Training and Support: Provide training and support to team members on transaction monitoring tools and AI/ML methodologies.
• Research: Stay updated on industry trends, emerging technologies, and best practices in transaction monitoring and AI/ML.

Requirements

• Experience: 3+ years of experience in transaction monitoring, fraud detection, or financial crime risk management, with a strong focus on AI/ML applications.
• Technical Skills: Proficiency in programming languages (e.g., Python, R), experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn), and familiarity with data visualization tools.
• Certifications: Relevant certifications (e.g., CAMS, CFE) are a plus.