风险经理 AI/生成式AI - 模型风险管理
Risk Manager AI/GenAI - Model Risk Management
高级分析师 - 模型风险管理 - KM07AE
分析师 - 模型风险管理 - KM08AE
我们致力于带来改变,并自豪于成为一家超越保障和政策的保险公司。在这里工作意味着拥有实现自己目标的机会,同时帮助他人也实现他们的目标。加入我们的团队,一起塑造未来。
精算与数据科学模型验证
哈特福德的模型风险管理职能正在寻找一名风险经理加入一个才华横溢、表现优异的模型风险管理团队。成功候选人将负责确保企业内使用的AI和生成式AI(GenAI)模型的完整性、准确性和合规性。风险经理/验证员将独立审查、质疑和验证模型,以确保其符合内部模型风险管理标准、监管期望和伦理AI原则。
哈特福德在各种重要且关键的业务功能中使用先进的分析、预测、AI/ML和生成式AI模型以及传统精算模型。模型风险管理团队通过验证这些模型、实施一致的政策和标准并保持适当的模型监督来管理哈特福德的模型风险。作为团队的一员,该职位将主要专注于验证哈特福德的AI和GenAI模型,并将结果报告给关键的内部利益相关者。其他职责包括教育建模最佳实践并在整个企业中推广模型风险意识。
职责:
在哈特福德的功能领域和业务线中对AI和GenAI模型使用案例进行模型验证,以确保模型有效且高效运行
- 确保模型计算、机器学习算法和GenAI方法准确且适用于预期用途
- 为诸如摘要、问答、搜索、数据合成、LLM作为评判者等任务设计和构建挑战解决方案和/或测试方法
- 审查和评估定量和定性测试技术,以确保模型的准确性、稳健性和可靠性
- 评估关键数据输入、假设、提示工程和上下文工程的准确性和适当性
- 审查模型输出的准确性及适当的下游使用情况
- 对关键建模要素进行有效挑战,如输入、计算、输出、概念合理性、监控与控制、文档等
查看英文原文
Sr Analyst Model Risk Management - KM07AEAnalyst Model Risk Management - KM08AEWe’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
Actuarial and Data Science Model Validation
The Hartford’s Model Risk Management function seeks a Risk Manager to join a talented and high-performing Model Risk Management team. The successful candidate will lead efforts to ensure the integrity, accuracy, and compliance of AI and Generative AI (GenAI) models used across the enterprise. The Risk Manager/Validator 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. As part of the team, this role will focus primarily on validating AI and GenAI models across The Hartford and reporting results to key internal stakeholders. Additional responsibilities include educating modeling best practices and spreading model risk awareness across the enterprise.
Responsibilities:
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.
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 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.
Compensation
The 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 - $162,000The posted salary range reflects our ability to hire at different position titles and levels depending on background and experience.
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Originally posted on Himalayas