Summary
Daniel Le is a Senior Principal Bioinformatics Scientist in the San Francisco Bay Area with a decade of experience applying statistics and machine learning to genomics and sequencing technology. He combines deep domain expertise from PhD-level chemical biology and postdoctoral work with practical engineering skills in R and Python to deliver interpretable, production-ready analyses. At Genentech and prior roles at CZ Biohub, Dovetail, and Stanford, he has led projects from assay development to neural-network–driven variant detection and single-cell transcriptome modeling. He emphasizes project ownership, mentoring, and clear visual communication to translate complex biology into stakeholder-ready insights. Known for bridging high-throughput experimental platforms with advanced computational models, he brings both hands-on assay experience and machine learning rigor to solve biological questions. Colleagues rely on him to turn ambiguous scientific problems into timely, actionable deliverables.
10 years of coding experience
6 years of employment as a software developer
California Polytechnic State University, San Luis Obispo
Doctor of Philosophy (PhD) Chemistry and Chemical Biology, Doctor of Philosophy (PhD) Chemistry and Chemical Biology at University of California, San Francisco
Vietnamese, English