Aig
insurance
AIModelValidationLead
Neural analysis suggests this role is
optimal for Senior candidates.
“AI Model Validation Lead at Aig. Skills: AI Model Validation, Machine Learning, Statistical Modeling, Risk Management. Design validation strategies. Execute validation strategies”
What You'll Achieve.
Ensure accuracy of AI models; Ensure robustness of AI models; Ensure ethical compliance of AI models; Transform risk management; Transform customer service; Support continuous improvement
Industry & Context.
Analytical mindset; Problem-solving skills
What They're Looking For.
Must Have
Master’s or PhD in Computer Science, Statistics, Mathematics, Engineering, or a related field, 10+ years of experience in AI/machine learning model validation, model risk management, or related roles, Expertise in supervised and unsupervised learning techniques, deep learning, natural language processing, and statistical modeling, Proficiency in programming languages such as Python, R, or Java, Familiarity with ML frameworks, Knowledge of data governance, ethical AI principles, and regulatory requirements impacting AI models, Experience with model validation tools, version control, and documentation best practices, Excellent analytical, problem-solving, and written communication skills, Ability to manage multiple projects and deadlines, working both independently and as part of a team
Nice to Have
Prior experience in insurance and/or financial services, healthcare, or regulated industries, Certification in model risk management or AI ethics, Demonstrated ability to lead complex validation projects and mentor junior team members
What You'll Do.
Design validation strategies
Execute validation strategies
Review model documentation
Conduct independent testing
Evaluate performance metrics
Perform sensitivity analyses
Perform stress testing
Challenge assumptions
Challenge data quality
Challenge methodology
Communicate model risks
Prepare validation reports
How You'll Work.
Team & Collaboration
Collaborate with data scientists; Collaborate with engineers; Collaborate with business stakeholders; Collaborate with cross-functional teams
Communication Scope
Excellent written communication skills
Process & Methodology
Manage multiple projects, Manage deadlines
Full Job Description
**AI Model Validation Lead** **Be part of something groundbreaking** At AIG, we are making long-term investments in a brand-new,**** innovative Generative AI team, designed to explore new possibilities for how artificial intelligence can be applied in insurance and beyond, and we need your help. With the support and investment needed to explore new frontiers in generative AI, you’ll be working alongside talented colleagues, innovating and leading projects that will transform how we manage risk and serve our customers. This team is central to our vision of the future and the core of our business offering. We will incorporate best-in-class engineering and product management principles and your guidance and collaboration will be critical to its success. To rapidly advance and innovate, we need your skills and expertise to build world-class products. If you’re excited by the opportunity to create meaningful impact at scale, we’d love to hear from you. **How you will create an impact** This role is responsible for ensuring the accuracy, robustness, and ethical compliance of artificial intelligence models deployed across the organization. This role requires a deep understanding of statistical modeling, machine learning algorithms, and risk management frameworks. The ideal candidate will work closely with data scientists, engineers, and business stakeholders to independently assess and validate models, document findings and recommend improvements. The position demands a strong analytical mindset, excellent communication skills, and the ability to manage multiple projects simultaneously in a fast-paced environment. ## * Design and execute comprehensive model validation strategies, including quantitative and qualitative assessments. * Review model development documentation, code, and datasets for correctness, completeness, and compliance with regulatory standards. * Conduct independent testing of AI models, evaluating performance metrics, sensitivity analyses, and stress tes
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