Model Risk Management Specialist
Validates and monitors AML/CFT transaction monitoring, customer risk assessment, screening, and AI models while assessing regulatory compliance, model risk, performance, and bias. Requires a quantitative bachelor's degree, 3+ years of relevant experience, and proficiency in Python, R, and SQL.
About the job
Responsibilities
- Independently validate Transaction Monitoring, Customer Risk Assessment, Screening, and AI models used for AML/CFT programs.
- Review pre- and post-development documentation, data quality, accuracy, access controls, and testing methodologies.
- Assess model performance, accuracy, stability, risk, and potential bias.
- Ensure models comply with EU AML/CFT Directives, US BSA/AML regulations, and FATF recommendations.
- Conduct AML/CFT model risk assessments, including analysis of higher-risk customer segments, products, geographies, controls, and mitigants.
- Develop procedures for ongoing model monitoring and maintenance, including annual reporting and certification, performance tracking, degradation detection, and regular reviews and updates.
- Collaborate with model engineers and owners, AML/CFT subject matter experts, business units, and risk management teams.
- Prepare model validation reports, risk assessments, and regulatory compliance reports.
- Develop and refine model validation frameworks and identify relevant best practices and industry standards.
Requirements
- Bachelor's degree in mathematics, statistics, computer science, engineering, or another quantitative field.
- 3+ years of experience in model validation, risk management, or a related field, preferably in AML/CFT.
- Strong understanding of machine learning and statistical modeling techniques.
- Deep understanding of fiat and crypto payment flows.
- Proficiency in Python, R, and SQL.
- Experience with data visualization tools such as Tableau or Power BI.
- Strong understanding of financial markets, products, and services.
- Excellent written and verbal communication skills, including the ability to explain complex technical concepts to non-technical stakeholders.
Nice-to-haves
- Professional certifications such as FRM, CDA, or CAP.
- Experience with AML/CFT transaction monitoring and Customer Risk Assessment systems.
- Knowledge of cloud-based technologies.
- Experience with agile development methodologies.
Skills
Model Validation, Transaction Monitoring, Customer Risk Assessment, Aml/Cft, Machine Learning, Statistical Modeling, Python, R, SQL, Tableau, Power BI, Risk Management, Cloud Technologies, Agile
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