Kristopher Simonsen

About

ML/AI engineer with strong healthcare insurance domain depth who has owned fraud detection and LLM claims products end-to-end in production. Stands out for combining modern MLOps and RAG architecture with measurable business impact, including millions in fraud savings, 40% faster analysis, and reusable platform tooling that accelerated multiple teams.

Key Strengths

• Owned production ML systems end-to-end from experimentation through deployment and monitoring
• Strong healthcare fraud and claims analytics domain expertise
• Delivered measurable fraud model impact: 25% accuracy improvement and 30% fewer false positives
• Improved investigation operations with 25% faster cycles and millions in annual savings
• Shipped LLM/RAG products with quality, latency, cost, and safety tradeoff management
• Built evaluation frameworks combining offline metrics and domain-expert review
• Implemented production AI safety controls including PHI masking and hallucination guardrails
• Iterative production optimization based on drift, feedback loops, and retrieval failures
• Designed reusable Python ML platform libraries adopted across multiple teams
• Improved team velocity and reliability: 40% faster feature engineering with fewer pipeline bugs
• Enabled self-service analytics for non-technical users with 40% faster analysis time

Experience

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