Quentin Spencer
Manager, Omnichannel Data Science
Lubbock, Texas, United States
Summary
👤
Senior🎓
Top SchoolQuentin Spencer is a seasoned data science leader with 19 years of experience marrying advanced signal-processing research and practical machine learning to fight fraud and authentication risk. Currently managing TransUnion’s Omnichannel Data Science team, he builds trusted inbound authentication and phone-takeover models that leverage large, heterogeneous data assets and modern techniques from tree ensembles to graph neural networks. His background spans radar and acoustic signal processing, power-line communications (with multiple patent applications), and early MIMO research—giving him a rare blend of theoretical rigor and production engineering. Comfortable across Hadoop/Spark, Python ML stacks, AWS and GCP, he champions graph ML as a high-leverage area for gains in fraud detection that traditional approaches miss. Based in Lubbock, Texas, Quentin combines deep academic training (PhD, BYU) with hands-on leadership in fraud systems used by financial services and telecom clients.
19 years of coding experience
17 years of employment as a software developer
PhD Electrical Engineering, PhD Electrical Engineering at Brigham Young University
Russian, GermanProgramming languages (1)
Github contributions (4)
qhspencer/lds-data-analysis
Oct 2018 - Jan 2023
Contributions:67 commits, 49 pushes, 1 branch in 4 years 4 months
qhspencer/SCOTUS
Oct 2020 - Apr 2022
Data and R code for "Comparative Mortality and Risk Factors for Death among US Supreme Court Justices (1789-2013)"
Contributions:5 pushes in 1 year 5 months
risklinear-modelsr-packagemortalityamong-us
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