VP, AI Governance & Model Validation

New York Life; New York (NY); Hybrid; USD 148,000 - 211,000; Full time

Job summary

New York Life is seeking a Corporate Vice President, Data Scientist - Model Validation and AI Governance to lead end-to-end validation across predictive, ML, generative, and agentic AI, with a focus on robust controls, guardrails, and governance. You will partner across risk, legal, and technology to translate requirements into practical validation practices.

The role demands deep quantitative expertise, strong risk judgment, and the ability to mentor colleagues while communicating complex

Qualifications

• 7+ years of model validation, governance, or risk management experience in regulated environments.
• Experience validating generative and agentic AI systems with multi-step workflows, tool use, and guardrails.
• Ability to design, build, or review AI evaluation frameworks and evidence for governance.
• Strong communication to translate complex findings for senior stakeholders.

Responsibilities

• Lead independent validation across predictive, ML, generative, and agentic AI solutions, assessing design, data pipelines, and evaluation metrics.
• Develop evaluation frameworks, benchmark datasets, and regression testing protocols.
• Establish monitoring, telemetry, and third‑party validation approaches with dashboards and alerts.
• Translate regulatory expectations into validation playbooks, SOPs, and evidence requirements.
• Mentor junior colleagues and present findings to governance bodies.

Skills

Statistical methods

ML validation

Generative/agentic AI

Python

SQL

Communication & leadership

Education

Advanced degree in Statistics, Computer Science, Data Science, Mathematics, Economics, Engineering or related quantitative discipline

Tools

Python

SQL

Job description

New York Life is seeking a Corporate Vice President, Data Scientist - Model Validation and AI Governance to lead end-to-end validation across predictive, ML, generative, and agentic AI, with a focus on robust controls, guardrails, and governance. You will partner across risk, legal, and technology to translate requirements into practical validation practices.

The role demands deep quantitative expertise, strong risk judgment, and the ability to mentor colleagues while communicating complex