Sampson M is a data scientist in the San Francisco Bay Area with 8 years of cross-disciplinary experience drawing on statistics, biology, and production analytics. He holds an M.S. in Statistical Science from UC Santa Cruz and has built end-to-end pipelines and spatial-deep-learning models to predict agricultural yields and improve biased spatial predictions. His background in next-generation sequencing and biostatistics led him to optimize RNA-seq pipelines and deploy machine learning models for cancer prediction, reducing processing time from days to hours. At public agencies and startups—including Climate, the FCC, and the IRS—he has translated complex survey and spatial data into actionable insights and reproducible code. Fast to learn and comfortable communicating technical results to stakeholders, he pairs research-grade modeling (Gaussian process and count-based spatial methods) with practical production skills. Colleagues rely on him for clear data narratives that bridge lab techniques and scalable statistical solutions.
8 years of coding experience
2 years of employment as a software developer
Bachelor’s Degree Astrophysics Molecular and Cell Biology , Bachelor’s Degree Astrophysics Molecular and Cell Biology at University of California, Berkeley
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