AI Model Risk Validation Specialist

The Mutual Group; New York (NY); Hybrid; USD 100,000 - 135,000; Full time

Benefits offered by this job

401(K) with company match

Medical, dental, vision

Wellness incentives

Paid time off

Educational assistance

Job summary

The Mutual Group in New York seeks an experienced AI/ML model validator to independently assess models across the organization and its carriers.

You will evaluate design, data quality, performance, bias, and explainability, and contribute to governance decisions. This role includes ongoing monitoring, documentation, and collaboration with risk and security teams.

Hybrid work options are available near the home office, with training and in-office days as needed.

Qualifications

• 5+ years in data science, model risk mgmt, or AI/ML validation.
• Experience with predictive models in regulated environments (insurance/financial services preferred).
• Strong understanding of machine learning models and statistical techniques.
• Familiarity with NAIC AI Model Bulletin, NIST AI RMF and governance standards.
• Ability to translate technical findings into business and risk implications.

Responsibilities

• Perform independent validation of AI/ML models, including design, methodology, and assumptions.
• Review data quality, training/test data representativeness, and performance metrics.
• Assess bias, explainability, and edge cases; identify model limitations.
• Provide input into AI governance decisions and support AIS/Security Governance with risk perspectives.
• Lead twice-annual validation and monitor drift, stability, and performance degradation.
• Ensure validation documentation is clear, traceable, and reproducible.
• Support inquiries with technical analysis and evidence.

Skills

Data science

Model risk management

AI/ML validation

Bias & fairness

Model lifecycle

NAIC AI Bulletin

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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