Actuarial and Data Science Model Validation – AI, Gen AI

The Hartford

Risk Manager for The Hartford's Model Risk Management function validating AI and GenAI models. Collaborate with Data Science for accurate model oversight and risk management.

Posted 6/10/2026full-timeHartford • Connecticut • 🇺🇸 United StatesMid-LevelSenior💰 $108,000 - $162,000 per yearWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Perform model validations models on AI and GenAI model use cases across The Hartford’s functional areas and lines of business to ensure models are performing effectively and efficiently
Ensure model calculations, machine learning algorithms, and GenAI 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 the quantitative and qualitative testing techniques to ensure model accuracy, robustness, and reliability
Assess key data inputs, assumptions, prompt engineering, context engineering for accuracy and appropriateness
Review model outputs for accuracy and appropriate downstream usage
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 existing GenAI model validation framework to include standardization 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, and regulatory expectations for emerging technologies and of department initiatives, deliverables, and reporting
Assist with the understanding and testing of cutting-edge tools, such as VertexAI/Google agent development kit, LangChain/LangGraph, RAG frameworks, HuggingFace, OpenAI APIs, etc.
Assist in improving The Hartford’s Model Risk Management function in relation to AI and GenAI, by monitoring external environment, implementing emerging best practices, recommending process improvements, and evolving standards/guidelines.

Requirements

What you’ll need

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 industry experience in machine learning or data science and with 1+ years focused on GenAI.
P&C, Group, Life or related insurance product experience is a plus
Strong programming experience across languages/technology platforms including Python, R, SAS/SQL
Solid understanding of GenAI concepts including prompt and context engineering, retrieval-augmented generation (RAG), agent workflow, LLM evaluation, familiarity with neural networks
Experience in GenAI tools such as Vertex AI/Google agent development kit, LangChain/LangGraph, RAG frameworks, HuggingFace, OpenAI APIs.
Ability to act independently with proactive self-directed accountability and demonstrated experience and consistency in meeting deadlines while adapting to shifting priorities
Strong analytical, critical and investigative thinking skills
Demonstrated commitment to lifelong learning with a strong desire for continuous development to keep pace with evolving modeling techniques and AI technologies.
Solution oriented creativity, innovative thinking, and challenging the status quo.
Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders across the enterprise.

Benefits

Comp & perks

Health insurance
Retirement plans
Flexible work arrangements
Professional development opportunities
Bonuses

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningGenAIprompt engineeringcontext engineeringdata synthesismodel validationquantitative testing techniquesanalytical thinkingprogramming (Python, R, SAS, SQL)neural networks

Soft Skills

proactive accountabilityanalytical skillscritical thinkinginvestigative thinkingsolution-oriented creativityinnovative thinkingcommunication skillscollaboration skillsadaptabilitylifelong learning

Certifications

M.S. in Artificial IntelligencePh.D. in Machine LearningM.S. in Computational ScienceM.S. in EngineeringM.S. in StatisticsM.S. in Applied MathematicsM.S. in Actuarial ScienceM.S. in Computer ScienceM.S. in Quantitative Economics