Thomas Mcclintock
Data Scientist
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolThomas Mcclintock is a Data Scientist in San Francisco with 10 years of experience applying machine learning and statistical methods to finance and industry problems. He transitioned from a PhD and postdoctoral research in cosmology—where he used Bayesian inference and large-scale simulations to study dark matter and dark energy—to building production ML systems at SIG, Cerebral, and now HubSpot. He combines high-performance computing and probabilistic modeling skills with hands-on experience deploying generative and serving models on AWS. Comfortable across research and product contexts, he enjoys collaborating with engineers and stakeholders to turn complex data into actionable solutions. A less obvious strength: his background in gravitational lensing and astronomical surveys informs a rigorous, simulation-driven approach to uncertainty quantification in ML.
11 years of coding experience
5 years of employment as a software developer
Master of Science - MS, High Performance Computing, Master of Science - MS, High Performance Computing at The University of EdinburghThe University of ArizonaBachelor of Arts - BA, Astrophysics, Bachelor of Arts - BA, Astrophysics at Amherst CollegeHigh School Diploma, High School Diploma at Harborfields High School
Github Skills (200)
cpython10
python10
testing10
pandas-dataframe10
cffi10
gtk10
density-estimation10
pypy10
data-cleaning10
mlmodel10
touches10
schema10
scientific-computing10
uniffi10
data-validation10
Programming languages (13)
Github contributions (5)
tmcclintock/Scratch-Work
Mar 2017 - Jul 2020
Contributions:138 pushes, 1 branch in 3 years 4 months
tmcclintock/Ultimate_statistics
Jun 2018 - Jan 2020
A small experiment to see how touches on an ultimate frisbee disc are distributed amongst players.
Contributions:11 commits, 1 PR, 9 pushes in 1 year 6 months
minecraftplayersfrisbeedisctouches
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