AI Model Risk Validator — Hybrid/Remote

The Mutual Group; Dallas (TX); Hybrid; USD 100,000 - 135,000; Full time

Benefits offered by this job

Competitive base salary plus incentive

401(K) with company match up to 6%

Comprehensive insurance options

Job summary

The Mutual Group seeks an independent validator of AI systems to assess model design, data quality, and performance against thresholds. You will review vendor documentation, contribute technical risk perspectives to governance, and lead twice-annual validation efforts while ensuring traceable, well-documented results.

Responsibilities include monitoring drift and degradation, supporting audits, and translating technical findings into business risk implications within a regulated insurance

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 validation methodologies.
• Bias and fairness concepts and model lifecycle management.
• Familiarity with NAIC AI Model Bulletin and NIST AI RMF.

Responsibilities

• Perform independent validation of AI/ML models including design, data quality, and benchmarks.
• Review vendor-provided documentation for completeness and accuracy.
• Lead governance input and provide technical risk perspectives during AI system reviews.
• Monitor AI systems for drift, stability, and performance degradation.
• Maintain validation documentation for audit and regulatory reviews.

Skills

ML explainability

Bias & fairness

Model evaluation

Risk implications

Job description

The Mutual Group seeks an independent validator of AI systems to assess model design, data quality, and performance against thresholds. You will review vendor documentation, contribute technical risk perspectives to governance, and lead twice-annual validation efforts while ensuring traceable, well-documented results.

Responsibilities include monitoring drift and degradation, supporting audits, and translating technical findings into business risk implications within a regulated insurance