Benjamin Stieger
Machine Learning Scientist, TPG Data Science
Geneva, Geneva, Switzerland
Summary
👤
Senior🎓
Top SchoolBenjamin Stieger is a machine learning scientist with 12 years of experience translating academic-grade data science into production ML products at Expedia Group, focused on revenue prediction, demand forecasting, and user intent modeling. He holds a PhD in Physics and spent much of his career at CERN and ETH Zürich developing large-scale data pipelines, statistical analyses, and innovative measurements in particle physics, including coordinating multi-team CMS analyses. Benjamin combines deep expertise in C++/ROOT and Python with hands-on experience building concurrent ingestion systems that processed terabytes per day, and he has applied those skills to industrial ML workflows and stakeholder-facing product ownership. He is an effective mentor and communicator who has supervised PhD students and led cross-disciplinary teams, and his open-source contributions to CMGTools-lite show a practical knack for improving analysis pipelines used in high-energy physics. Unusually for an industry ML practitioner, he brings first-hand experience in experimental hardware run-control and data acquisition, giving him a systems-aware perspective on model reliability and deployment.
12 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at Eidgenössische Technische Hochschule Zürich
German, English, French
Github Skills (7)
root-view10
c-language10
high-energy-physics10
cprogramming-language10
document-root10
data-analysis10
git4
Programming languages (4)
Github contributions (5)
CERN-PH-CMG/cmgtools-lite
Feb 2016 - Jan 2017
CMGTools as a subsystem, not as a CMSSW overlay
Role in this project:
Back-end Developer
Back-end DeveloperContributions:101 commits, 7 PRs, 9 comments in 11 months
Contributions summary:Benjamin primarily worked on the development and modification of C++ code related to high-energy physics analysis within the CMGTools-lite repository. Their contributions include updates and modifications to the code for generating friend trees and calculating btag scale factors. Further work included adjusting the mass fitting process of the data and the application of PU weights. These changes indicate a focus on improving data analysis pipelines within the context of a particle physics experiment.
subsystemcmsswoverlay
stiegerb/cms-htcondor-es
Jul 2017 - May 2019
ElasticSearch integration for CMS's HTCondor pool
Contributions:7 PRs, 131 pushes, 106 branches in 1 year 9 months
cmshtcondorpoolelasticsearchelasticsearch-integration
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