Paul Reidy
Software Engineer at Amazon Web Services (AWS)
Ireland
Summary
👤
Senior🎓
Top SchoolPaul Reidy is a Software Engineer at AWS in Dublin with nine years of experience bridging data science and software engineering, particularly in machine learning, security, and privacy. He holds MSc degrees in Computer Science and Economics and has applied rigorous research methods from academia (UCD Complex Software Lab) to production problems at Accenture and AWS. His background includes building scalable data pipelines and anomaly detection models for financial fraud, survival and time-series forecasting for mortgage pre-payment, and hands-on work with Spark, Scala, R and large-scale systems. An active open-source contributor, he has improved documentation and fixed bugs in the widely used pandas library, demonstrating attention to reproducibility and developer experience. Colleagues describe him as a pragmatic problem-solver who pairs analytical depth with clean, production-ready code.
9 years of coding experience
3 years of employment as a software developer
Master of Science (MSc), Economics, Distinction, Master of Science (MSc), Economics, Distinction at Trinity College DublinMaster of Science - MSc, Computer Science, First Class Honours, Master of Science - MSc, Computer Science, First Class Honours at University College Dublin
Stackoverflow
1reputation
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Github Skills (5)
pandas10
data-science10
data-analysis10
python9
documentation8
Programming languages (3)
Github contributions (5)
pandas-dev/pandas
Oct 2017 - Mar 2019
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:
Data Scientist
Data ScientistContributions:40 commits, 38 PRs, 116 comments in 1 year 5 months
Contributions summary:Paul primarily contributed to the documentation and code related to the pandas library. The user clarified documentation for various functions like `describe`, and examples. Furthermore, the user addressed specific bugs by raising value errors. Additionally, they added examples to update docstrings, and improved documentation surrounding functions such as `truncate` and `resample`.
pythondatalabeled-datamanipulationdataframes
reidy-p/pandas
Oct 2017 - Jul 2019
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:436 pushes, 89 branches in 1 year 9 months
polarspythondatalabeled-datamanipulation
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