Alex Goodman
Data Scientist III
Greater Chicago Area United States
Summary
👤
Senior🎓
Top SchoolAlex Goodman is a Data Scientist III at NASA Jet Propulsion Laboratory with 13 years of experience applying scientific software engineering to remote sensing and climate challenges. He builds production-ready pipelines and petascale Zarr datasets, optimizes ML workflows (including random-forest feature engineering for Mars imagery), and prototypes cloud-scale analysis tools using Dask, zarr, kerchunk and STAC. Alex blends research and operational impact—his atmospheric river outlooks were used by California water managers and he helped run ARSET trainings for nearly 1,000 participants. An active open-source contributor, he enhanced Apache Zeppelin’s Python/matplotlib integration to enable inline plotting across Python 2/3, improving interactive notebook UX. Based in the Greater Chicago area, he combines atmospheric science training (MS, Colorado State) with hands-on engineering to make large-scale geospatial data more accessible and analyzable.
12 years of coding experience
8 years of employment as a software developer
Master of Science (MS) Atmospheric Science, Master of Science (MS) Atmospheric Science at Colorado State UniversityBachelor of Science (BS) Atmospheric Sciences, Bachelor of Science (BS) Atmospheric Sciences at University of Illinois Urbana-Champaign
Github Skills (12)
data-visualizations10
data-visualization10
data-visualisation10
python10
matplotlib10
back-end-development9
javascript6
testing5
big-data5
javas4
java4
scala4
Programming languages (9)
Github contributions (5)
apache/zeppelin
Jan 2017 - Jan 2017
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Role in this project:
Back-end Developer & UI Engineer
Back-end Developer & UI EngineerContributions:1 commit, 17 PRs, 61 comments in 1 day
Contributions summary:Alex contributed to the Apache Zeppelin project by enhancing the Python interpreter's matplotlib integration. They implemented support for displaying PNG images, addressing Python 2 and 3 compatibility issues. Furthermore, the user introduced a custom matplotlib backend to natively support inline plotting within the interpreter, and fixed a bug related to dynamic forms not working after a prior update. These changes improved the user experience and functionality of the Python environment within Zeppelin.
data-drivendata-analyticsanalyticsnosqlflink
agoodm/climate
Jun 2016 - Nov 2018
Contributions:83 pushes, 42 branches in 2 years 5 months
javaclimateapacheworkbench
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