Summary
Jordan Sorokin is a Staff Data Scientist in computational biology with a decade of experience blending neuroscience, machine learning, and software engineering to accelerate biological discovery. Trained as a neuroscientist (PhD, Stanford) and skilled in computational/applied math, he has bridged wet-lab experiments and production-scale analysis—leading cross-functional teams at Recursion and shaping disease programs and scalable image-processing pipelines at Herophilus. His work spans hierarchical mixed-effects modeling, parallelized AWS deployments, and large-scale neural data analysis, with peer-reviewed publications and an active GitHub demonstrating applied research code. Known for mentoring and translating complex biology into reproducible data products, he brings both hands-on experimental insight and production ML rigor to problems in neural circuits and disease biology. An uncommon strength is his track record of guiding experimental design from hypothesis to deployed algorithms, shortening the loop between bench and computation.
10 years of coding experience
5 years of employment as a software developer
Computational and Applied Mathematics, Computational and Applied Mathematics at Woods Hole Oceanographic Institution
Doctor of Philosophy (Ph.D.), Neurobiology and Neurosciences, Doctor of Philosophy (Ph.D.), Neurobiology and Neurosciences at Stanford University School of Medicine
BA, Neurobiology and Neurosciences, 3.71, BA, Neurobiology and Neurosciences, 3.71 at University of Pennsylvania
Spanish, English