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Sr Analyst Model Risk & AI, Gen AI Model Validation
Job in
Hartford, Hartford County, Connecticut, 06112, USA
Listed on 2026-10-09
Listing for:
The Hartford
Full Time
position Listed on 2026-10-09
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), AI Evaluation, Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
**** 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.−
Identify findings and recommendations, including impact analysis, to mitigate model risk and compile clear and concise model validation reports
* Perform governance accountabilities related to findings tracking, remediation testing, and validation
* Assist in enhancing the existing GenAI model validation framework to include standardized evaluation metrics for performance and reliability, deployment of model validation tools for increased efficiency, and ensure continued alignment with regulatory standards
* Strengthen partnerships with Data Science teams to keep model risk practices aligned with the proliferation and sophistication of modeling, promote proactive risk management, and share best practices.
* Pro-actively stay informed with advancements in AI/ML, GenAI, agentic systems, and regulatory expectations for emerging technologies and of department initiatives, deliverables, and reporting
* Assist with the evaluation and testing of cutting-edge tools, such as VertexAI/Google Agent Development Kit (ADK), Lang Chain/Lang Graph, RAG frameworks, Hugging Face, OpenAI APIs, etc.
* Assess solution alignment with internal AI Governance standards, Model Risk Management policies, and emerging regulatory expectations.
*
* Qualifications:
*** Advanced degree (M.S. or Ph.D.) in a relevant field e.g. Artificial Intelligence, Machine Learning, Computational Science, Engineering, Statistics, Applied Mathematics, Actuarial Science, Computer Science, Quantitative Economics.
* 3+ years of…
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