Kasey Schultz is a Senior Data Scientist in San Diego with 12 years of experience blending physics rigor and production ML to solve complex operational problems. With a PhD in Physics, she has moved from high-performance geophysical simulations to deploying multimodal LLM and deep learning systems at scale—most recently orchestrating multi-agent workflows and simulation-driven decision support across 40+ hospitals at Kaiser Permanente. Previously at Intuit she cut data-entry time in half, drove multimodal semantic search that slashed dataset sourcing from weeks to minutes, and consolidated classifiers to save >$100k/year while boosting F1 substantially. She also advises an ocean-energy startup, applying AI to wave-powered IoT, reflecting a rare combination of domain science, NLP/LLM expertise, and product-focused engineering. Colleagues rely on her ability to translate research-grade models into robust, cost-effective production systems that deliver measurable business impact.
12 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at University of California, Davis
Bachelor of Science (BS), Physics, Mathematics, Bachelor of Science (BS), Physics, Mathematics at University of Miami
Contributions:81 commits, 73 pushes in 2 years 3 months
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