Kenneth Tay
Quantitative Researcher
Singapore, Singapore
Summary
👤
Senior🎓
Top SchoolKenneth Tay is a quantitative researcher with 12 years of experience blending statistics, AI and public policy, now at Jump Trading after leading optimization and causal-inference efforts at LinkedIn. A Stanford PhD in Statistics, he has built production-grade tooling—internal Python and R packages—for contextual bandits and observational causal inference that materially sped deployment and raised analytical standards. His work at LinkedIn delivered one of the platform’s largest marketing metric improvements and practical runbooks for productionizing bandits, while earlier roles at Google, Amazon (A9) and Singapore government agencies reflect a rare mix of high-scale engineering, robust experimentation, and policy-facing analytics. Outside pure research he has run a small consultancy (Inherent Journey) and brings experience translating complex methods into operational products and decision frameworks.
12 years of coding experience
8 years of employment as a software developer
AB, Mathematics, AB, Mathematics at Princeton UniversityGCE A Levels, Mathematics, Physics, Chemistry, GCE A Levels, Mathematics, Physics, Chemistry at Anglo-Chinese Junior CollegeDoctor of Philosophy (Ph.D.), Statistics, Doctor of Philosophy (Ph.D.), Statistics at Stanford University
Github Skills (20)
r-package9
cran8
delphi8
effort8
r8
decomposition8
optimization-methods7
unit-testing7
solver7
frame6
mixed-integer-programming6
optimization5
regression5
testing5
python5
Programming languages (5)
Github contributions (5)
kjytay/FIFA-world-cup-2018
Jun 2018 - Jul 2018
Contributions:23 commits, 19 pushes, 1 branch in 25 days
kjytay/stanford-stats
Nov 2016 - Apr 2018
Contributions:45 commits, 41 pushes, 1 branch in 1 year 5 months
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