ScottĀ Hendrickson
Director Data Science, Data Accelerator
Denver, Colorado, United States
Summary
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Top SchoolScott Hendrickson is a data science leader with 14 years of experience building teams and internal data products that accelerate performance, security, and scalability across enterprise organizations. As Director of Data Science, Data Accelerator at F5 (and previously leading data and engineering functions at Aspen Mesh, Notion, and Twitter), he blends hands-on analytics, AI product strategy, and physics-based modeling to turn complex data into operational advantage. He has a track record of recruiting and empowering cross-functional teams of analysts, data scientists, and engineers to deliver reliable, evolving data products and measurable business impact. His work spans from foundational notebooks that teach core ML techniques to enterprise-grade data services, reflecting both mentorship and technical depth. Based in Denver with a PhD in physics, Scott brings a scientific rigor and curiosity to product strategy and storytelling with data. An uncommon strength is his ability to combine academic modeling instincts with pragmatic product delivery to explain and improve real-world systems.
14 years of coding experience
24 years of employment as a software developer
PhD, PhD at University Of Colorado-BoulderBS, BS at Walla Walla CollegeCampion Academy
Stackoverflow
400reputation
39kreached
19answers
0questions
Github Skills (12)
k-means-clustering10
machine-learning10
python10
data-analysis9
deserialization6
multiprocessing6
floating-point6
bson6
unicode6
numpy6
binary-files6
cgi6
Programming languages (1)
Github contributions (5)
DrSkippy/Data-Science-45min-Intros
Sep 2013 - Oct 2017
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques
Role in this project:
Data Scientist
Data ScientistContributions:112 commits, 47 PRs, 78 pushes in 4 years 1 month
Contributions summary:Scott contributed to the implementation of K-means clustering and maximum likelihood estimation, as evidenced by the added notebook. Additionally, the user updated the maximum likelihood notebook, which included changes to the plotted distributions. Further changes were made after a team review, indicating iterative development.
techniquesstatisticspythondata-sciencejupyter-notebook
DrSkippy/Python-DP-Means-Clustering
Jun 2012 - Dec 2014
Contributions:18 commits in 2 years 5 months
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