Hans Niederhausen
Applied Scientist at Amazon
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolHans Niederhausen is an applied scientist with 11 years of experience turning cutting-edge machine learning and statistical methods into scientific and operational impact. Currently at Amazon SCOT/OSS in Seattle, he applies research-grade modeling to supply chain optimization and sourcing decisions. His prior work includes postdoctoral and research roles that led to high-profile discoveries of astrophysical neutrino sources and publications in Science and Physical Review Letters. Hans combines deep expertise in probabilistic inference, maximum-likelihood/Bayesian methods, and deep learning for particle reconstruction with a track record of moving algorithms from research into production. Notably, he earned the 2023 Shakti Duggal Award and helped develop tools used across the IceCube collaboration, showing an unusual blend of large-scale scientific collaboration experience and product-focused delivery. He holds a PhD in Physics from Stony Brook University and brings rigorous experimental thinking to complex, data-driven engineering problems.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at The Julius Maximilians University of WürzburgDoctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Stony Brook University
Github Skills (50)
r9
cascade9
kaggle8
classification8
python8
equation8
lightgbm8
data-mining8
gradient8
parallel8
gradient-boosting7
machine-learning7
ranking7
decision-tree7
high-performance6
Programming languages (4)
Github contributions (5)
HansN87/ReferencePriors
Nov 2015 - Feb 2017
Contributions:8 PRs, 25 pushes, 2 branches in 1 year 2 months
HansN87/DiffuseCascadeFit
Jan 2015 - Dec 2015
Contributions:20 PRs, 28 pushes, 24 branches in 10 months
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