Summary
Samantha Zeitlin is a founder and technical leader with 12+ years blending scientific rigor and production machine learning, currently running Radically Different Data Science and leading engineering at Tribe AI. A PhD-trained biochemist turned self-taught Pythonista, she specializes in making the invisible visible through analytics, ML, and scalable data infrastructure (favorites: Pandas, Seaborn, Neo4j, Pachyderm). Her background spans hands-on research, product engineering, and managing data teams at companies like Elastic and Sentry, plus volunteer work with U.S. Digital Response. She consults across technical design, developer relations, hiring, and career mentoring, bringing both deep domain knowledge and practical delivery. Recent work includes cloud-native tooling such as Google Pub/Sub, BigQuery, Kubernetes, and Pachyderm, reflecting a focus on reproducible, production ML pipelines. Unusually for someone with her academic pedigree, she emphasizes pragmatic engineering over bioinformatics, pairing published research with production-grade code.
12 years of coding experience
8 years of employment as a software developer
Coursera
Udacity
self-taught python, self-taught python at way too much school
PhD Molecular and Cellular Structure and Chemistry, PhD Molecular and Cellular Structure and Chemistry at Scripps Research
Thomas Jefferson High School for Science and Technology
BA Biochemistry, BA Biochemistry at University of Pennsylvania
Stanford Open EdX
French