Artificial Intelligence Lead - Insurance Domain Responsibilities
* Develop and execute a comprehensive AI strategy aligned with Insurance business objectives (growth, loss ratio optimization, customer retention, operational efficiency).
* Identify and prioritize high-impact AI and GenAI use cases across the insurance value chain, including:
o Underwriting automation and risk scoring
o Pricing optimization and actuarial modeling enhancement
o Claims automation and fraud detection
o Customer service virtual assistants and policy servicing
o Document intelligence for policy and claims processing
* Design and deploy AI-powered solutions to improve combined ratio, customer experience, and operational scalability.
* Lead cross-functional teams (Data Science, IT, Actuarial, Risk, Operations, Compliance) in AI solution design and integration.
* Oversee development, validation, and monitoring of machine learning models for predictive analytics and risk modeling.
* Ensure compliance with insurance regulatory frameworks, model governance standards, data privacy laws, and ethical AI principles.
* Drive AI research, prototyping, and proof‑of‑concept initiatives focused on insurance innovation.
* Establish and manage partnerships with AI technology vendors, insurtech firms, and research institutions.
* Promote AI literacy and change management across Insurance business units.
Professional Experience
* Proven experience with GenAI and AI/ML applications in Insurance. (Required)
* 8+ years of experience in AI/ML roles with strong applied problem-solving background. (Required)
* 5+ years of experience in Insurance (Life, P&C, Health, or Reinsurance) or insurance technology. (Required)
* Demonstrated experience implementing AI/ML solutions in underwriting, pricing, claims, fraud, or customer analytics. (Required)
* Experience leading large-scale AI programs and managing multidisciplinary teams. (Required)
* Strong understanding of actuarial concepts, risk modeling, and insurance KPIs (loss ratio, combined ratio, retention, claims leakage). (Required)
Education
* BSc or MSc degree in Computer Science, Artificial Intelligence, Mathematics, Actuarial Science, Engineering, or related quantitative field. (Required)
* AI/ML, cloud, or data science certifications. (Preferred)
Languages
* Fluent English and Spanish (Required)
Hard Skills
* Expert-level knowledge of machine learning algorithms and predictive modeling.
* Strong understanding of GenAI, LLM applications, and prompt engineering in regulated environments.
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