Omar Jabri
Lead AI Scientist at Target
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolOmar Jabri is a Lead AI Scientist based in Sunnyvale with seven years of applied experience building demand forecasting and statistical systems for major retailers. He blends a strong academic foundation in statistics and economics from UC Berkeley with hands-on roles spanning statistician work at DemandTec to data science at MBO Partners and enterprise AI leadership at Target. His background includes a stint at JP Morgan–reflected in his GitHub bio–indicating experience bridging finance-grade rigor and large-scale retail forecasting. Omar focuses on turning probabilistic models into production-ready forecasts that drive inventory and merchandising decisions. He’s comfortable operating at the intersection of classical statistics, machine learning, and engineering, and often brings robotics-inspired rigor to automation and pipeline reliability. Colleagues describe him as pragmatic and detail-oriented, able to translate complex models into measurable business impact.
7 years of coding experience
5 years of employment as a software developer
BA, Statistics, Economics, BA, Statistics, Economics at University of California, Berkeley
Github Skills (43)
ivy10
pytorch10
python10
translation10
converter10
mxnet10
machine-learning10
abstraction10
numpy10
deep-learning10
tensorflow10
gpu10
data-science9
ocr9
tesseract9
Programming languages (4)
Github contributions (5)
OmarJabri7/ivy_fork_v1
Apr 2023 - Sep 2023
The Unified Machine Learning Framework
Contributions:4 PRs, 40 pushes, 16 branches in 4 months
OmarJabri7/Bio-Signal-Artifact-Removal
Jun 2021 - Nov 2023
In this repository, I will support the work of a PhD student in removing noise in EEG signals by using an AI algorithm for real-time noise reduction. <br> This Algorithm is used on generated EEG signals (Synthetic/Fake) in which the contents are known, allowing for a better algorithm benchmark.
Contributions:9 PRs, 90 pushes, 3 branches in 2 years 5 months
deep-learningbenchmarkreductionnoise-reductionai-algorithm
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