Summary
Jason Lai is a Lead Data Science Consultant and AI Architect with 10 years’ experience building production ML and GenAI platforms across life sciences, consumer products, and energy—especially in regulated, high-compliance settings. He architects reusable LLM frameworks (agentic workflows, RAG, code execution) and has driven adoption of governed GenAI solutions across large pharma programs, balancing privacy, validation, and latency constraints. Jason has led multi-agent systems for clinical research and post-market device monitoring, and scaled ML from prototype to production for biotech startups and enterprise clients. He pairs deep computational biology roots (PhD and postdoc work on protein modeling and Rosetta contributions) with practical engineering—shipping real-time vision pipelines, CI/CD for R/R&D reproducibility, and cross-platform apps. An experienced people manager, he mentors and aligns small technical teams to sustained delivery, and off-hours competes in table tennis at an international level.
10 years of coding experience
11 years of employment as a software developer
Bachelor's degree Biomedical Engineering (Biomedical Informatics), Bachelor's degree Biomedical Engineering (Biomedical Informatics) at Arizona State University
Postdoctorate Pharmacology (Computational Biophysics), Postdoctorate Pharmacology (Computational Biophysics) at Baylor College of Medicine
Doctor of Philosophy - PhD Molecular Biology (Bioinformatics Computational Chemistry), Doctor of Philosophy - PhD Molecular Biology (Bioinformatics Computational Chemistry) at University of Wyoming