Model Risk & AI Validation Analyst

Rekruitd; Chicago (IL); On-site; USD 80,000 - 120,000; Full time

Job summary

Rekruitd in Chicago is seeking a Model Risk & AI Validation Analyst for a full-time, permanent role that supports independent validation and governance of quantitative models, machine learning solutions, and AI systems.

You will evaluate model soundness, data integrity, implementation accuracy, and performance while coordinating remediation with stakeholders and regulatory reviews. The ideal candidate has 2-5 years in model validation or risk management, with advanced degree preferred.

Qualifications

• 2–5 years of experience in model validation, development, or risk management.
• Experience in banking or financial services model validation.
• Experience with AI/ML and/or quantitative models.
• Knowledge of validation methodologies: conceptual soundness, performance benchmarking, sensitivity analysis, and assumptions testing.

Responsibilities

• Independently validate quantitative models, machine learning solutions, and AI systems.
• Evaluate methodology, data integrity, assumptions and limitations, implementation accuracy, and model performance.
• Perform quantitative testing including back-testing, sensitivity analysis, scenario analysis, benchmarking, and performance testing.
• Review model development, methodology, testing, governance, and supporting documentation.
• Identify model weaknesses, limitations, and areas requiring remediation.
• Provide independent challenge and clearly communicate validation findings to model owners and business stakeholders.
• Support model governance, validation reporting, and regulatory review activities.
• Track findings and work with stakeholders through remediation.

Skills

Quantitative analysis

Documentation

Communication

Analytical thinking

Model risk management

Education

Master's degree or PhD in a quantitative or related discipline

Job description

Seeking a Model Risk & AI Validation Analyst for a full-time, permanent opportunity. This position will support the independent validation and governance of quantitative models, machine learning solutions, and AI systems.

• Independently validate quantitative models, machine learning solutions, and AI systems
• Evaluate model methodology, conceptual soundness, data integrity, assumptions and limitations, implementation accuracy, and model performance
• Perform quantitative testing including back-testing, sensitivity analysis, scenario analysis, benchmarking, and performance testing
• Review model development, methodology, testing, governance, and supporting documentation
• Identify model weaknesses, limitations, and areas requiring remediation
• Provide independent challenge and clearly communicate validation findings to model owners and business stakeholders
• Support model governance, validation reporting, and regulatory review activities
• Track findings and work with stakeholders through remediation

Experience:

• 2-5 years of experience in model validation, model development, model risk management, data science, AI, or machine learning
• Model validation or development experience within banking or financial services
• Experience working with AI/ML and/or quantitative models
• Experience with banking risk models, including areas such as credit, financial forecasting, regulatory compliance, CECL, liquidity, or financial crime
• Knowledge of model validation methodologies including conceptual soundness, model performance, benchmarking, sensitivity analysis, and assumptions/limitations testing
• Strong quantitative, analytical, documentation, and communication skills
• Master's degree or PhD in a quantitative or related discipline preferred