Model Validation Specialist – AML Transaction Monitoring

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

📋 Description

• Execute independent validation of AML and Financial Crime models.

• Perform threshold tuning and optimization of AML transaction monitoring scenarios.

• Assess model methodologies, assumptions, data quality, and performance metrics.

• Create validation documentation, such as validation reports, model assessments, playbooks, and runbooks.

• Analyze extensive datasets to discover trends, anomalies, and opportunities for model enhancement.

• Evaluate risks linked to model design, implementation, and ongoing monitoring processes.

• Offer recommendations for model enhancements, process improvements, and risk mitigation.

• Collaborate with Compliance, Financial Crime, Technology, and Business teams on model governance initiatives.

• Keep track of regulatory changes and industry trends concerning AML, BSA, sanctions screening, and financial crime analytics.

• Present findings, recommendations, and validation results to stakeholders and senior management.

• Assist in the implementation and validation of new detection scenarios, models, and monitoring strategies.

• Utilize data analytics and statistical methods to assess model performance and suspicious activity detection capabilities.

• Deliver assessments that comply with regulatory standards and enhance financial crime detection capabilities.

⛳️ Requirements

• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Data Science, Economics, Finance, Computer Science, or a related area.

• 5-8 years of experience in AML Model Validation, Model Risk Management, Financial Crime Analytics, or Transaction Monitoring.

• In-depth understanding of AML regulations and compliance frameworks, including BSA, AML Directives, and relevant regulatory requirements.

• Demonstrated expertise in AML Transaction Monitoring threshold tuning and optimization.

• Practical experience validating financial crime models and evaluating model performance.

• Strong knowledge of model governance, validation methodologies, and principles of model risk management.

• Experience in creating validation reports, model documentation, playbooks, and operational runbooks.

• Exceptional analytical, quantitative, and statistical problem-solving abilities.

• Advanced SQL proficiency and experience handling large datasets.

• Proficient in Python and/or R for data analysis and model validation tasks.

• Experience with data mining, exploratory data analysis, and statistical evaluations.

• Outstanding verbal and written communication skills, capable of conveying complex findings to both technical and non-technical audiences.

• Strong presentation skills and stakeholder management capabilities.

• Comprehensive understanding of banking products, services, and financial crime risks across various business lines.

🏝️ Benefits

• Competitive compensation and benefits package.

• Meaningful opportunities for career development.

• Diverse and inclusive workplace culture.

• Engaging and challenging work environment.

• Continuous learning and growth opportunities.