Daniel Smith
Machine Learning Engineer at Cash App
Oakland, California, United States
Summary
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Top SchoolDaniel Smith is a Machine Learning Engineer at Cash App / Block with eight years of experience applying ML and quantitative methods across finance and scientific research. He has transitioned model risk and credit underwriting expertise from roles at Block and Bank of America into production-focused model lifecycle automation at Cash App. A PhD physicist who ran multi-terabyte simulations and published across neutrino experiments, he brings rigorous experimental design, HPC, and software engineering to ML systems. His background includes deploying CNNs and GANs for particle detectors at CERN and building core reconstruction code at Fermilab, evidence of a rare mix of domain science and production ML. Based in Oakland, he combines regulated-finance model defensibility with hands-on automation to move complex models from research to reliable production.
7 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of ChicagoBachelor of Arts - BA Physics, Bachelor of Arts - BA Physics at Boston University
English, Spanish
Github Skills (6)
neutrino10
spectrum10
detectors9
monte-carlo9
simulation9
energy3
Programming languages (2)
Github contributions (5)
dansmithphysics/dansmithphysics.github.io
Jun 2018 - Feb 2020
Contributions:14 pushes, 1 branch in 1 year 7 months
dansmithphysics/rnog_vpol_fat_dipole
May 2021 - Mar 2022
Contributions:9 pushes, 1 branch in 9 months
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