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Senior, niche ML/NLP/GenAI role with domain constraints reduces applicant density.
Strong insurance domain, compliance, and enterprise AI governance requirements increase background specificity and reduce transferability.
Extensive mandatory ML/GenAI/NLP skills, cloud platform experience, and insurance governance make filters highly stringent.
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Lead end-to-end development and operationalization of advanced AI, machine learning, and business intelligence solutions, including statistical modeling and conversational AI deployments.
Design and implement evaluation and monitoring frameworks for AI and BI models, tracking key performance indicators and enabling A/B testing and drift detection.
Operate within regulated insurance industry settings, ensuring AI analytics solutions comply with governance, privacy, and ethical standards while supporting strategy and business outcomes.
Proven experience in statistical modeling, machine learning, advanced analytics using Python (pandas, NumPy, scikit-learn), and strong SQL skills.
Experience with conversational AI and generative AI applications including document parsing, RAG pipelines, prompt engineering, and cloud-based AI platforms like Google Vertex AI, AWS SageMaker, or Azure AI.
Foundational knowledge of insurance domain including underwriting, claims, pricing, and regulatory compliance.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in managing complete AI/ML lifecycle from requirements through production monitoring within enterprise and regulated environments.
Demonstrates strong technical communication skills to translate complex AI models and results to diverse business stakeholders effectively.
Proficient in advanced NLP, Generative AI methods, and integration of AI solutions with business intelligence and data warehouse environments in insurance context.