Sr Model Validation Analyst - AI & Predictive Models
Burtch Works, New York, NY, United States
Job Title
Senior Model Validation Analyst – AI & Predictive Models Location
Hybrid – 3 days per week onsite (NYC) Type
Permanent Pay Rate
$150,000 – $190,000 per year About the Company
We are a Fortune 100 mutual financial services organization with a long‑standing legacy of purpose, integrity, and innovation. As we continue evolving into a technology, data, and AI‑enabled enterprise, we remain committed to delivering meaningful impact for our customers and communities. Our AI & Data organization partners across business, technology, and risk functions to ensure responsible AI adoption, sound governance, and measurable business value. We offer a collaborative, inclusive environment where forward‑thinking professionals can contribute to transformative initiatives while building long‑term careers. Job Summary
We are seeking a Senior Model Validation Analyst to join the Artificial Intelligence & Data organization. This role focuses on model validation and governance for predictive and AI/ML models within a regulated environment. The ideal candidate will bring strong statistical expertise, hands‑on modeling knowledge, and experience translating regulatory and risk requirements into practical validation controls. This individual will partner closely with Model Risk Management (MRM), data science teams, and business stakeholders to ensure models are robust, compliant, and aligned to enterprise risk standards. Key Responsibilities
Methodology Review & Challenge: Review model design, data pipelines, feature engineering, and evaluation metrics. Challenge assumptions and assess appropriateness of modeling methodologies. Parallel Validation & Challenger Modeling: Replicate model results, compare alternative methodologies, build challenger models where appropriate, and evaluate business impact and associated risks. Documentation & Reporting: Develop rigorous validation reports and create executive‑level summaries that clearly communicate complex statistical findings in accessible narratives and visuals. Risk & Controls Translation: Interpret technical regulatory documentation and translate requirements into validation checklists, standard operating procedures, and control evidence documentation. Post‑Deployment Monitoring: Define monitoring criteria for model drift, bias/fairness, stability, hallucinations (for AI systems), and overall business KPI performance. Partner with teams to operationalize automated alerts. Standards & Enablement: Contribute to shared templates, playbooks, guidelines, and reusable validation frameworks for predictive, generative, and agentic AI use cases. Industry Awareness: Stay current on statistical modeling, AI/ML methodologies, regulatory expectations, and emerging risk considerations. Requirements
Education
Advanced degree in Statistics, Computer Science, Data Science, Mathematics, Economics, Engineering, or related quantitative field. Experience
4+ years of experience in model validation, model governance, or model risk management. Experience validating predictive and AI/ML models in regulated environments. Exposure to financial services or insurance industry preferred. Skills
Strong understanding of statistical modeling techniques (linear/logistic regression, survival analysis, GLMs, GAMs). Experience with modern ML methods (GBM/XGBoost, neural networks, feature engineering/selection). Proficiency in Python and SQL. Knowledge of bias testing, stress testing, root cause analysis, and model performance evaluation. Ability to interpret regulatory guidance and translate into validation controls. Strong written and verbal communication skills. Certifications
Not required. Other
Strong attention to detail and regulatory awareness. Collaborative mindset and ability to work cross‑functionally. Proactive approach to continuous learning and AI literacy. Preferred Qualifications
Experience evaluating Generative AI systems, including prompting strategies and Retrieval‑Augmented Generation (RAG). Knowledge of stress testing, model interpretability, privacy, and security considerations for AI systems. Conceptual understanding of Reinforcement Learning. Experience collaborating with Legal, Compliance, and Cybersecurity review bodies. Practical understanding of AI use cases in financial services (e.g., underwriting, claims, fraud detection, marketing analytics, customer service automation). Compensation
Salary Range:
$150,000 – $190,000 annually Overtime Eligible:
Exempt Discretionary Bonus Eligible:
Yes Actual base salary will be determined based on experience, skills, qualifications, and location. Employees may also be eligible for annual discretionary and incentive programs. Benefits
Competitive Compensation:
Market‑aligned salary with performance‑based incentives. Health and Wellness:
Comprehensive medical, dental, and wellness programs. Work‑Life Balance:
Hybrid work arrangement with supportive leave programs. Professional Development:
Ongoing training in AI, governance, and risk best practices. Additional Perks:
Adoption assistance, student loan repayment programs, employee giving and volunteer initiatives.
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Senior Model Validation Analyst – AI & Predictive Models Location
Hybrid – 3 days per week onsite (NYC) Type
Permanent Pay Rate
$150,000 – $190,000 per year About the Company
We are a Fortune 100 mutual financial services organization with a long‑standing legacy of purpose, integrity, and innovation. As we continue evolving into a technology, data, and AI‑enabled enterprise, we remain committed to delivering meaningful impact for our customers and communities. Our AI & Data organization partners across business, technology, and risk functions to ensure responsible AI adoption, sound governance, and measurable business value. We offer a collaborative, inclusive environment where forward‑thinking professionals can contribute to transformative initiatives while building long‑term careers. Job Summary
We are seeking a Senior Model Validation Analyst to join the Artificial Intelligence & Data organization. This role focuses on model validation and governance for predictive and AI/ML models within a regulated environment. The ideal candidate will bring strong statistical expertise, hands‑on modeling knowledge, and experience translating regulatory and risk requirements into practical validation controls. This individual will partner closely with Model Risk Management (MRM), data science teams, and business stakeholders to ensure models are robust, compliant, and aligned to enterprise risk standards. Key Responsibilities
Methodology Review & Challenge: Review model design, data pipelines, feature engineering, and evaluation metrics. Challenge assumptions and assess appropriateness of modeling methodologies. Parallel Validation & Challenger Modeling: Replicate model results, compare alternative methodologies, build challenger models where appropriate, and evaluate business impact and associated risks. Documentation & Reporting: Develop rigorous validation reports and create executive‑level summaries that clearly communicate complex statistical findings in accessible narratives and visuals. Risk & Controls Translation: Interpret technical regulatory documentation and translate requirements into validation checklists, standard operating procedures, and control evidence documentation. Post‑Deployment Monitoring: Define monitoring criteria for model drift, bias/fairness, stability, hallucinations (for AI systems), and overall business KPI performance. Partner with teams to operationalize automated alerts. Standards & Enablement: Contribute to shared templates, playbooks, guidelines, and reusable validation frameworks for predictive, generative, and agentic AI use cases. Industry Awareness: Stay current on statistical modeling, AI/ML methodologies, regulatory expectations, and emerging risk considerations. Requirements
Education
Advanced degree in Statistics, Computer Science, Data Science, Mathematics, Economics, Engineering, or related quantitative field. Experience
4+ years of experience in model validation, model governance, or model risk management. Experience validating predictive and AI/ML models in regulated environments. Exposure to financial services or insurance industry preferred. Skills
Strong understanding of statistical modeling techniques (linear/logistic regression, survival analysis, GLMs, GAMs). Experience with modern ML methods (GBM/XGBoost, neural networks, feature engineering/selection). Proficiency in Python and SQL. Knowledge of bias testing, stress testing, root cause analysis, and model performance evaluation. Ability to interpret regulatory guidance and translate into validation controls. Strong written and verbal communication skills. Certifications
Not required. Other
Strong attention to detail and regulatory awareness. Collaborative mindset and ability to work cross‑functionally. Proactive approach to continuous learning and AI literacy. Preferred Qualifications
Experience evaluating Generative AI systems, including prompting strategies and Retrieval‑Augmented Generation (RAG). Knowledge of stress testing, model interpretability, privacy, and security considerations for AI systems. Conceptual understanding of Reinforcement Learning. Experience collaborating with Legal, Compliance, and Cybersecurity review bodies. Practical understanding of AI use cases in financial services (e.g., underwriting, claims, fraud detection, marketing analytics, customer service automation). Compensation
Salary Range:
$150,000 – $190,000 annually Overtime Eligible:
Exempt Discretionary Bonus Eligible:
Yes Actual base salary will be determined based on experience, skills, qualifications, and location. Employees may also be eligible for annual discretionary and incentive programs. Benefits
Competitive Compensation:
Market‑aligned salary with performance‑based incentives. Health and Wellness:
Comprehensive medical, dental, and wellness programs. Work‑Life Balance:
Hybrid work arrangement with supportive leave programs. Professional Development:
Ongoing training in AI, governance, and risk best practices. Additional Perks:
Adoption assistance, student loan repayment programs, employee giving and volunteer initiatives.
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