Austin O'boyle is a software engineer with nine years of experience combining academic research in autonomous vehicles, controls, and navigation with practical industry work building and deploying production web applications. A Queen's University physics graduate with strong math and CS foundations, he has spent 2+ years shipping React/Node.js apps on cloud platforms like AWS and Bluemix and contributes to open-source tooling. His GitHub work includes improving a LinkedIn scraping package by refactoring, adding logging, and hardening data extraction—signals of a pragmatic backend developer who values maintainability and reliability. Based in Palo Alto and affiliated with Google on GitHub, he blends research rigor with hands-on engineering to solve real-world problems end-to-end.
9 years of coding experience
9-12, 9-12 at Don Mills Collegiate Institute
Bachelor of Science - BS, Physics, 4.0/4.3, Bachelor of Science - BS, Physics, 4.0/4.3 at Queen's University
`scrape_linkedin` is a python package that allows you to scrape personal LinkedIn profiles & company pages - turning the data into structured json.
Role in this project:
Backend Developer
Contributions:8 reviews, 12 commits, 15 PRs in 1 year 4 months
Contributions summary:Austin primarily focused on improving the functionality and maintainability of the `scrape-linkedin-selenium` package. Their contributions include refactoring the code by removing dependencies on internal APIs and adding logging capabilities to multiple files. They also fixed bugs related to profile scraping by addressing issues in the data extraction process and improving the handling of potential errors. Furthermore, they introduced enhancements like auto-formatting imports and refactoring the company scraper to fetch page HTML.
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