AI Model Risk Validation Specialist

The Mutual Group; Chicago (IL); Hybrid; USD 100,000 - 135,000; Full time

Benefits offered by this job

Competitive base salary with incentive

401(k) with company match up to 6%

Life/AD&D, long-term & short-term dis.

Medical, dental, vision

Wellness incentives

Generous time off & volunteer PTO

Hybrid/remote options

Educational assistance

Job summary

The Mutual Group is seeking an experienced validator to independently assess AI/ML models across the organization. You will evaluate model design, data quality, performance thresholds, and regulatory alignment, acting as a second-line reviewer in governance decisions.

You will lead semi-annual validations, monitor drift and performance, and ensure documentation is clear, traceable, and audit-ready. This role offers hybrid/remote options for eligible employees within commuting distance.

Qualifications

• 5+ years in data science, model risk management, or AI/ML validation.
• Experience with predictive models in regulated environments (insurance/financial services preferable).
• Strong understanding of ML models, evaluation methods, bias concepts, and lifecycle management.
• Familiarity with NAIC AI Model Bulletin, NIST AI RMF, and governance standards.

Responsibilities

• Perform independent validation of AI/ML models, including design, data quality, performance metrics, and benchmarking.
• Review vendor-provided FactSheets and technical documentation for completeness and accuracy.
• Evaluate key model risks, including bias, explainability, and edge cases.
• Provide validation input into AI governance decisions and support AIS/Security Governance.
• Lead twice-annual validation and monitor drift, stability, and performance degradation.
• Maintain validation documentation for audits and regulatory reviews.

Skills

Data science

Model risk management

AI/ML validation

Bias and fairness

Explainability

Job description

Job Description

Serve as the independent validator of AI Systems, responsible for technical assessment, model risk evaluation, and ongoing monitoring of AI/ML models across The Mutual Group and its member insurance carriers.

Department

Information Technology

Work Arrangement

Employees who live within 30 miles of the TMG home office are expected to follow a hybrid or in-office schedule. The initial training period may require additional in-office days.

Accountabilities

Model Validation (Core Responsibility)

• Perform independent validation of AI/ML models, including:
• Model design, methodology, and assumptions
• Training and test data quality and representativeness
• Performance metrics, thresholds, and benchmarking
• Review vendor-provided FactSheets and technical documentation for completeness and accuracy

Risk Assessment

• Evaluate key model risks, including:
• Bias and fairness
• Explainability and interpretability
• Model limitations and edge cases
• Assess alignment with:
• NAIC expectations
• Model risk management practices
• Identify gaps and recommend risk mitigation strategies

Governance Integration

• Provide independent validation input into AI governance decisions
• Support the AIS / Security Governance Team by contributing technical risk perspectives during AI system reviews
• Act as a second-line reviewer to challenge assumptions and strengthen decision-making

Ongoing Monitoring

• Lead twice-annual validation of AI Systems
• Monitor predictive models for:
• Drift
• Stability
• Performance degradation
• Ensure monitoring practices align with AIS Program requirements
• Recommend corrective actions when performance or risk thresholds are breached

Documentation & Audit Support

• Maintain model validation documentation for:
• Internal audit
• Regulatory review
• Ensure validation results are:
• Clearly documented
• Traceable and reproducible
• Support inquiries with technical analysis and evidence

Qualifications

• 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
• Model evaluation and validation methodologies
• Bias and fairness concepts
• Model lifecycle management
• Familiarity with:
• NAIC AI Model Bulletin
• NIST AI RMF
• Model governance and validation standards
• Ability to translate technical findings into business and risk implications

Pay Range

Anticipated Hiring Range:

• $100,000 - $135,000 annual base salary depending on experience, qualifications, and geographic location

Benefits

• Competitive base salary plus incentive plans for eligible team members
• 401(K) retirement plan that includes a company match of up to 6% of your eligible salary
• Free basic life and AD&D, long-term disability and short-term disability insurance
• Medical, dental and vision plans to meet your unique healthcare needs
• Wellness incentives
• Generous time off program that includes personal, holiday and volunteer paid time off
• Flexible work schedules and hybrid/remote options for eligible positions
• Educational assistance

Equal Opportunity Employer

The Mutual Group is an Equal Opportunity Employer. It is our policy to recruit, hire, train and promote individuals in all job classifications without regard to race, color, religion, sex, national origin, age, veteran status, disability, sexual orientation, gender identity or any other characteristic protected by law.

• Know Your Rights: Workplace Discrimination is Illegal
• Your Rights Under USERRA

Applicants requiring a reasonable accommodation due to a disability at any stage of the employment application process should contact [e-mail].

Employment Verification

The Mutual Group participates in the E-Verify program and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. You are protected from employment discrimination based on your citizenship status and national origin.

E-Verify Program Overview

E-Verify Participation Poster

All offers of employment are contingent upon the successful completion of a background check.

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