Shane Lubold
Senior Applied Scientist at LinkedIn
Sunnyvale, California, United States
Summary
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Senior🎓
Top SchoolShane Lubold is a Senior Applied Scientist with 11 years of experience applying statistics and machine learning to real-world problems, now building causal and behavioral models at LinkedIn after research roles at Amazon and the U.S. Census Bureau. He earned a PhD in Statistics from the University of Washington, where he developed Bayesian and network-embedding methods, designed survey approaches that cut costs by 70%, and published in top journals like JRSS-B. Shane combines strong computational skills in Python, R, MATLAB, and SQL with a track record of making algorithms run substantially faster for large datasets and mentoring junior researchers. His applied work spans causal inference, reinforcement learning, NLP, and Monte Carlo methods, with past projects fusing multi-sensor data and producing goodness-of-fit tests for Bayesian state estimators. Known for translating theoretical advances into production-ready code and scalable experiments, he’s comfortable operating at the intersection of research, engineering, and product. Based in Sunnyvale, he brings both academic rigor and measurable impact on billion-scale analytics systems.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Statistics, Doctor of Philosophy - PhD Statistics at University of WashingtonBachelor of Science - BS Math, Bachelor of Science - BS Math at Arizona State UniversityProgramming languages (2)
Github contributions (5)
slubold/slubold.github.io
Dec 2020 - May 2024
Minimal is a Jekyll theme for GitHub Pages
Contributions:209 pushes in 3 years 5 months
jekylljekyll-theme
slubold/Networks-Reading-Group
Jul 2020 - Jul 2020
Contributions:20 commits, 19 pushes, 1 branch in 2 days
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