Scott Executive
Director - Hardware Strategy Planning
Boise, Idaho, United States
Summary
🤩
Rockstar🎓
Top SchoolScott Executive is a strategic technology and business leader with 11 years of experience blending hardware strategy, product development, and data science leadership, currently directing Hardware Strategy Planning at Microsoft from Boise. He has a proven track record of building high-performance teams that drive profitability across innovation, manufacturing, M&A, and go-to-market execution, and advises BridgeTower Capital on technology and investment decisions. Hands-on in cloud and ML infrastructure, Scott has contributed to high-profile open-source projects such as Ray and Vowpal Wabbit—implementing Azure autoscaling and improving Python/Scikit-learn integrations—highlighting his ability to bridge enterprise hardware strategy with practical software and deployment engineering. He pairs an Executive MBA with technical roots in electronics engineering, and is noted for translating complex technical constraints into executable roadmaps and profitable joint ventures.
11 years of coding experience
Certification, Micro MBA, Certification, Micro MBA at Boise State UniversityBS, Electronics Engineering Technology, BS, Electronics Engineering Technology at DeVry University
Github Skills (27)
autoscaling10
recommendation-system10
deploying10
python10
evaluation10
elearning10
scikit10
machine-learning10
cloud-infrastructure10
microsoft-azure10
eval10
aac10
scikit-learn10
infrastructure-as-code10
azure10
Programming languages (12)
Github contributions (5)
recommenders-team/recommenders
Dec 2018 - Oct 2021
Best Practices on Recommendation Systems
Role in this project:
ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:150 reviews, 505 commits, 130 PRs in 2 years 10 months
Contributions summary:Scott's commits focus on updating and refining definitions and implementations for model evaluation metrics, specifically recall. They clarified the definition of recall@k in the code. The user also contributed a new notebook detailing a deep dive into Vowpal Wabbit and its application to recommendation tasks and worked on issues with using the code in that notebook..
recommendation-systemspythonjupyter-notebookoperationalizationmicrosoft
ray-project/ray
Mar 2020 - Aug 2022
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:Cloud Engineer
Cloud EngineerContributions:28 reviews, 8 commits, 8 PRs in 2 years 5 months
Contributions summary:Scott primarily contributed to the Azure autoscaler within the Ray project. Their work involved implementing Azure support, including node provider functionality, Azure Resource Manager template integration, and authentication updates using azure-identity based authentication. Contributions extended to fixing deployment issues, addressing naming problems, and resolving deletion delays, showcasing a focus on cloud infrastructure and deployment automation.
pythonconsistsruntimetensorflowserving
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