AI Model Risk Validation Specialist

Jobtailor; Illinois; On-site; USD 120,000 - 180,000; Full time

Job summary

The Mutual Group seeks an experienced AI/ML validation professional to act as an independent validator across its AI systems and insurer partners. You will assess model design, data quality, performance metrics, thresholds, and benchmarking, and report risks with mitigation actions.

Responsibilities include reviewing vendor documentation, evaluating bias, fairness, and alignment with NAIC and NIST guidance, while maintaining reproducible validation records for audits and governance decisions.

Qualifications

• 5+ years in data science, model risk management, or AI/ML validation.
• Experience with predictive models in regulated environments; insurance or financial services preferred.
• Strong understanding of machine learning models and statistical techniques.
• Strong understanding of model evaluation and validation methodologies.
• Strong understanding of bias and fairness concepts.
• Strong understanding of model lifecycle management.
• Familiarity with NAIC AI Model Bulletin and NIST AI RMF.

Responsibilities

• Act as independent validator of AI Systems and their governance decisions.
• Review design, methodology, data quality, performance metrics, thresholds, and benchmarking.
• Evaluate bias, fairness, explainability, limitations, and edge cases.
• Maintain validation documentation for internal audit and regulatory review.
• Identify gaps and recommend risk mitigation actions.
• Lead periodic validation of AI systems and monitor drift and performance.

Skills

AI/ML validation

Model risk management

Data science

Tools

NAIC AI Model Bulletin

NIST AI RMF

Model governance standards

Job description

• Serve as the independent validator of AI Systems across The Mutual Group and its member insurance carriers
• Perform independent validation of AI/ML models, including model design, methodology, assumptions, data quality, representativeness, performance metrics, thresholds, and benchmarking
• Review vendor-provided FactSheets and technical documentation
• Evaluate bias, fairness, explainability, interpretability, limitations, and edge cases
• Assess alignment with NAIC expectations and model risk management practices
• Identify gaps and recommend risk mitigation strategies
• Provide independent validation input into AI governance decisions
• Support the AIS / Security Governance Team during AI system reviews
• Act as a second-line reviewer to challenge assumptions and strengthen decision-making
• Lead twice-annual validation of AI Systems
• Monitor models for drift, stability, and performance degradation
• Recommend corrective actions when performance or risk thresholds are breached
• Maintain validation documentation for internal audit and regulatory review
• Ensure validation results are clearly documented, traceable, and reproducible
• Support inquiries with technical analysis and evidence

Requirements

• 5+ years in data science, model risk management, or AI/ML validation
• Experience working with predictive models in regulated environments; insurance or financial services preferred
• Strong understanding of machine learning models and statistical techniques
• Strong understanding of model evaluation and validation methodologies
• Strong understanding of bias and fairness concepts
• Strong understanding of model lifecycle management
• Familiarity with NAIC AI Model Bulletin
• Familiarity with NIST AI RMF
• Familiarity with model governance and validation standards
• Ability to translate technical findings into business and risk implications
• Must be authorized to work in the U.S.
• Successful completion of a background check required

Core Competencies

Demonstrates expertise in AI/ML model validation, including evaluation methodologies, bias and fairness concepts, and model lifecycle management. Proficient in translating technical findings into business implications while ensuring compliance with regulatory standards.

Highest-signal resume keywords

• AI/ML Model Validation
• Model Risk Management
• Bias And Fairness Evaluation
• Model Lifecycle Management
• Regulatory Compliance

Hard Skills

• Data Science
• Predictive Modeling
• Statistical Techniques
• Model Evaluation MethodologiesPerformance Metrics
• Risk Mitigation Strategies
• Validation Documentation
• Technical Analysis
• Model Monitoring
• Benchmarking

Soft Skills

• Decision-Making
• Communication
• Critical Thinking
• Problem-Solving

Industry Keywords

• Insurance
• Financial Services
• Regulated Environments
• Model Governance
• Validation Standards

Tools & Technologies

• NAIC AI Model Bulletin
• NIST AI RMF