Loan review specialist with ML exp

Role: Loan review specialist with ML exp

Location: Seattle WA Onsite

Key Responsibilities

1 Traditional Loan Review Responsibilities

• Conduct independent reviews of commercial, consumer, real estate, agricultural, and specialty loan portfolios.
• Evaluate borrower financial condition, repayment capacity, collateral adequacy, and overall creditworthiness.
• Validate the accuracy and appropriateness of assigned risk ratings and recommend adjustments when necessary.
• Assess compliance with internal credit policies, underwriting standards, and loan documentation requirements.
• Identify emerging risks, trends, and concentrations within the loan portfolio.
• Review loan documentation for completeness, accuracy, and regulatory sufficiency.
• Prepare written reports summarizing findings, exceptions, and recommendations for management and the Board.
• Monitor remediation efforts and follow up on previously identified issues.

2 MachineLearning (ML) Model Responsibilities

• Review MLgenerated credit decisions, risk scores, or earlywarning indicators to ensure they align with prudent creditrisk principles.
• Assess the reasonableness of ML model outputs, including identifying anomalies, outliers, or inconsistent riskrating assignments.
• Evaluate data quality used in ML models for completeness, accuracy, and relevance to creditrisk assessment.
• Verify that MLdriven recommendations are appropriately validated by human review and do not override sound underwriting judgment.
• Monitor for potential model bias, disparate impacts, or unintended discriminatory patterns in MLbased credit decisions.
• Collaborate with modelrisk management teams to understand model assumptions, limitations, validation results, and performance metrics.
• Review model documentation to ensure transparency, explainability, and compliance with regulatory expectations for model governance.
• Provide feedback on how ML tools impact credit quality, underwriting consistency, and portfoliolevel risk trends.
• Maintain independence by evaluating MLbased decisions with the same rigor applied to manual underwriting.

• 3 7 years of experience in loan review, credit analysis, commercial lending, or banking risk management.
• Exposure to modelrisk management, data analytics, or MLbased credit tools is preferred.

• Ability to challenge both human and modelgenerated decisions constructively.