Gregory Rome is a Senior Counsel and technology-savvy attorney based in New Orleans with nine years of professional experience bridging law, IT, and vendor management. He leads commercial transactions and supports customer growth projects at Entergy, having previously run enterprise software asset management, vendor alliances, and audit defense programs that delivered measurable cost savings. Before corporate practice he founded and managed a general practice law firm handling litigation, estate planning, and business counseling, and earlier operated an IT services company building software and infrastructure for small businesses. Gregory combines hands-on software development and systems administration experience with JD and advanced business training, enabling him to translate technical scope into robust commercial agreements and governance. An active contributor to the pandas open-source project, he has improved data-serialization tests and modernized type annotations, a detail that underscores his practical expertise in data tooling and code quality. This blend of legal, commercial, and engineering fluency makes him adept at resolving disputes, negotiating complex tech contracts, and designing operational controls that reduce risk and cost.
9 years of coding experience
14 years of employment as a software developer
Computer Science, Computer Science at Georgia Institute of Technology
BS, Computer science, Political science, BS, Computer science, Political science at Loyola University New Orleans
Master of Business Administration - MBA, Finance, Master of Business Administration - MBA, Finance at University of Louisiana at Lafayette
JD, Law, Civil law, JD, Law, Civil law at Tulane University Law School
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:
Back-end Developer / Data Scientist
Contributions:15 commits, 15 PRs, 86 comments in 2 months
Contributions summary:Gregory primarily contributed to fixing bugs and improving type annotations within the pandas library. Their work involved correcting flakiness in test cases related to the `to_stata` functionality, indicating familiarity with data serialization and testing procedures. They also updated type hints using Python3 syntax across several pandas modules, especially in `core/array`, enhancing code readability and maintainability. This suggests a focus on improving the library's robustness and code quality.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Contributions:83 pushes, 29 branches in 2 months
polarspythondatalabeled-datamanipulation
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