Fidan Uz
Principal Data Science And Engineering Manager
Edgewater, New Jersey, United States
Summary
🤩
Rockstar🎓
Top SchoolFidan Uz is a Principal Group Data Science Manager with 10+ years building end-to-end AI systems at Microsoft, leading Americas-facing teams to deliver co-engineered solutions across manufacturing, retail, energy and automotive industries. She combines deep technical expertise in machine learning, computer vision and mathematical optimization with hands-on deployment experience to turn complex research into production-grade analytics and object-detection solutions. Her background spans academia (PhD in Decision Information Sciences and former assistant professorship) and industry, giving her a rare blend of theoretical rigor and customer-facing product delivery. Known for translating domain-specific constraints into scalable models and optimization pipelines, she excels at aligning technical choices with clear business impact. Based in Edgewater, NJ, she brings both strategic leadership and the practical instincts of a seasoned applied data scientist.
10 years of coding experience
22 years of employment as a software developer
Bachelor of Science (BS) Electrical and Electronics Engineering, Bachelor of Science (BS) Electrical and Electronics Engineering at Middle East Technical UniversityPh. D Decision Information Sciences, Ph. D Decision Information Sciences at University of Florida - Warrington College Of Business
English
Github Skills (54)
pytorch10
convolutional-neural-networks10
python10
microsoft10
image-processing10
architecture10
machine-learning10
similarity10
predictive10
azure-architecture10
cortana10
object-detection10
computer-vision10
jupyter-notebook10
azure10
Programming languages (7)
Github contributions (5)
microsoft/AKSDeploymentTutorial
Mar 2018 - Feb 2019
Tutorial on how to deploy Deep Learning models on GPU enabled Kubernetes cluster
Contributions:33 commits, 13 PRs, 13 pushes in 10 months
deep-learninggpukubernetes-clustertensorflowkubernetes
Azure/lstms_for_predictive_maintenance
May 2017 - Jul 2017
LSTMS for Predictive Maintenance
Contributions:22 commits, 3 PRs, 2 pushes in 2 months
predictivepredictive-maintenancelstmsmaintenance
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