Ray Bell
AI ML Product Director at State of Maryland
Annapolis, Maryland, United States
Summary
🤩
Rockstar🎓
Top SchoolRay Bell is an AI/ML Product Director with nine years of experience translating climate science and oceanographic research into production AI products for government and industry. Holding a PhD in Atmosphere, Oceans and Climate, he has led enterprise AI teams at DTN and Royal Caribbean to deliver data-driven SaaS solutions across weather, agriculture, energy and shipping, and now directs AI/ML product strategy for the State of Maryland. He blends domain expertise in sub-seasonal and seasonal forecasting with hands-on engineering—contributing to open-source projects like numba, dask, xarray and cudf as a documentation and backend contributor—so complex scientific models become reliable, usable tools. Known for improving developer and user-facing documentation and CI automation in major scientific libraries, he quietly boosts adoption by making sophisticated tooling approachable. Based in Annapolis, he pairs academic rigor with pragmatic product leadership to move climate-informed AI from research into operational impact.
9 years of coding experience
10 years of employment as a software developer
PhD. Atmosphere Oceans and Climate Tropical Cyclones and Climate Change, PhD. Atmosphere Oceans and Climate Tropical Cyclones and Climate Change at University of ReadingMOcean Oceanography, MOcean Oceanography at University of Southampton
English, Spanish
Stackoverflow
1,558reputation
155kreached
15answers
47questions
Github Skills (52)
conda-forge10
github-ci10
batching10
restructuredtext10
jupyterhub10
python10
sphinx10
trajectory-generation10
pandas10
xray10
geopandas10
analyse10
bash10
rs10
geospatial10
Programming languages (19)
Github contributions (5)
dask/dask
Dec 2017 - Oct 2024
Parallel computing with task scheduling
Role in this project:
Technical Writer
Technical WriterContributions:2 reviews, 20 PRs, 48 comments in 6 years 10 months
Contributions summary:Ray primarily contributed to the project's documentation. Their commits focused on updating existing documentation, adding new examples, and clarifying instructions for developers and users. The changes included updates to installation procedures, examples of using functions, and the addition of examples for using features like `dask-sql`. They were also involved in hyperlinking and improving the structure of documentation.
pythonschedulingparallelnumpydask
movingpandas/movingpandas
Nov 2021 - Dec 2022
Movement trajectory classes and functions built on top of GeoPandas
Role in this project:Back-end Developer
Back-end DeveloperContributions:9 reviews, 34 commits, 47 PRs in 1 year 1 month
Contributions summary:Ray primarily contributed to the `movingpandas` library by adding new functionalities related to trajectory analysis. Their work included adding features such as the ability to add and manipulate speed, direction, and acceleration columns to trajectory dataframes. They also refactored existing code and added new modes for trajectory splitting based on time intervals, and updated documentation. These modifications involved changes to core classes and tests within the library.
movement-datapythondasktrajectoryon-top
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