Sr Analyst Model Risk & AI, Gen AI Model Validation

Sr Analyst Model Risk Management - KM07AE

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Sr Analyst Model Risk & AI, Gen AI Model Validation

Overview of the Position

The Hartford’s Model Risk Management function seeks a Senior Analyst to join a talented and high-performing Model Risk Management team. The successful candidate will lead model validation efforts of Generative AI (GenAI) and agentic AI models used across the enterprise. The candidate will independently review, challenge, and validate models to ensure they meet internal model risk management standards, regulatory expectations, and ethical AI principles.

The Hartford utilizes advanced analytics, predictive, AI/ML, and Generative AI models as well as traditional actuarial models in a variety of important and critical business functions. The Model Risk Management team manages model risk across The Hartford by validating these models, implementing consistent policies and standards, and maintaining appropriate model oversight.

This role will focus primarily on reviewing, challenging, and validating GenAI and agentic AI models across The Hartford and reporting results to key internal stakeholders. Additional responsibilities include developing modeling best practices and spreading model risk awareness across the enterprise.

Responsibilities:

• Perform model validations on GenAI and agentic AI model use cases across The Hartford’s functional areas and lines of business to ensure models are performing effectively and efficiently
• −        Ensure model calculations, algorithms, and methods are accurate and appropriate for intended use
• −        Design and build challenger solutions and/or testing methods for tasks such as summarization, question answering, search, data synthesis, LLM-as-a-judge etc.
• −        Review and assess quantitative and qualitative testing techniques to ensure model accuracy, robustness, and reliability
• −        Assess key data inputs, assumptions, prompt engineering, and context engineering for accuracy and appropriateness
• −        Design and execute testing approaches appropriate for non-deterministic AI systems, including variability analysis, confidence intervals, and statistical evaluation methodologies.
• −        Deliver effective challenge to key modeling elements such as inputs, calculations, outputs, conceptual soundness, monitoring & controls, documentation, etc.