Douglas Davis
Machine Learning Engineer, Senior Consultant Level at Visa
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolDouglas Davis is a machine learning engineer with 11 years of experience who builds high-throughput, low-latency inference platforms and backend systems, currently leading real-time fraud detection engineering at Visa. He brings deep expertise in Python and Rust and a strong track record contributing to the PyData ecosystem—most notably improving Dask’s array and dataframe capabilities and distributed scheduler extensibility. His background includes open-source R&D at Anaconda and core contributions to dask-awkward and dask-histogram, reflecting a focus on scalable data pipelines and numerical tooling. Douglas earned a PhD in Elementary Particle Physics from Duke, where he engineered performant data processing and ML classifiers for ATLAS, an experience that shaped his transition into software engineering. He combines research rigor with production-grade engineering, comfortable moving between algorithm design, systems optimization, and developer-facing APIs. Based in Austin, he also maintains a technical blog at ddavis.io that surfaces practical insights from both research and large-scale engineering.
11 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy - PhD, Elementary Particle Physics, Doctor of Philosophy - PhD, Elementary Particle Physics at Duke UniversityBachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at The University of Texas at Austin
Stackoverflow
347reputation
29kreached
6answers
10questions
Github Skills (20)
scheduled-tasks10
python10
job-scheduler10
testing10
pandas10
plugin10
numpy10
scheduler10
distributed-computing10
scheduling10
sched10
dask10
task-scheduler10
job-scheduling10
pytest9
Programming languages (10)
Github contributions (5)
dask/dask
Apr 2019 - Jun 2023
Parallel computing with task scheduling
Role in this project:
Back-end Developer
Back-end DeveloperContributions:74 reviews, 26 PRs, 159 comments in 4 years 3 months
Contributions summary:Douglas primarily contributed to the Dask library, focusing on improving the `array` and `dataframe` modules. Their work included fixing documentation issues, adding support for new features such as multidimensional histograms, and refactoring existing code to handle different data types and input formats. Furthermore, they addressed bugs, improved test coverage, and enhanced the consistency of the API, contributing to the overall stability and usability of the library.
pythonschedulingparallelnumpydask
dask/distributed
Mar 2021 - Oct 2022
A distributed task scheduler for Dask
Role in this project:Back-end Developer
Back-end DeveloperContributions:22 reviews, 8 commits, 9 PRs in 1 year 7 months
Contributions summary:Douglas contributed to the Dask distributed task scheduler, focusing on enhancements and plugin integrations. They added documentation to the `dashboard_link` property in the client and refactored scheduler plugin storage. The user also added support for registering scheduler plugins from the client, improving the system's extensibility and flexibility. They also made changes to avoid repeatedly using the same worker on the first task, potentially improving performance.
pythonschedulerdaskdistributed-computingdistributed-systems
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.