Daniel Wiesenthal is a Staff Data Scientist and machine learning leader with a decade of experience turning research-grade AI and HCI insight into production data products and recommendation systems. He pairs an MS in Computer Science and BS in Symbolic Systems from Stanford with hands-on engineering—cofounding and CTOing multiple startups and shipping end-to-end ML pipelines at Stitch Fix to optimize assortment, sizing, and personalized recommendations. Comfortable bridging technical and non-technical stakeholders, he has led teams, taught immersive data science programs, and created scalable, interpretable systems that centralize metrics and align cross-functional business needs. His background in linguistics, cognitive psychology, and early research on sentiment flowing through networks gives him a rare ability to design models that prioritize human experience as much as predictive performance. Outside work he’s driven by entrepreneurship, teaching, and a love of coffee—so he’s equally likely to debug a model or spark a new collaboration over a cup.
10 years of coding experience
8 years of employment as a software developer
Swahili Studies and Coastal Cultures of East Africa, Swahili Studies and Coastal Cultures of East Africa at SIT Study Abroad
International Baccalaureate, International Baccalaureate at French American International High School
BS, Symbolic Systems, BS, Symbolic Systems at Stanford University
Contributions:10 PRs, 35 pushes, 10 branches in 3 months
flaskpythonbase-structure
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Daniel Wiesenthal - Staff Data Scientist, Machine Learning