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.
- 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), LangChain/LangGraph, RAG frameworks, HuggingFace, 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 industry experience in machine learning or data science with 1+ years focused on GenAI and/or agentic AI.
- P&C, Group, Life or related insurance product experience is a plus
- Strong programming and technology experience across languages/ platforms including Python, SQL, and Git.
- Solid understanding of GenAI concepts including prompt and context engineering, retrieval-augmented generation (RAG), LLM internals, LLM evaluations, and multi-agent systems.
- Experience in modern cloud and AI tools such as GCP/Vertex AI, Google uAgent Development Kit (ADK), AWS/SageMaker, LangChain/LangGraph, 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.
CompensationThe listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$108,000 - $162,000
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
