Maxine Whitely is a founding member of the technical staff at an early-stage startup in New York with nine years of software engineering experience spanning health tech, journalism, and platform tooling. She has built server-side health features at Apple and driven growth engineering at Levels, applying biosensor data to real-time user experiences. Her open-source work includes backend contributions to The New York Times’ documentation tooling and City Bureau’s city-scrapers, where she implemented authentication, robust scraping pipelines, and data-cleaning logic. Comfortable across Python, backend systems, and data ingestion, she focuses on reliable access control and preserving content integrity at scale. As a former CS teaching lead, she pairs production experience with clear technical communication and a knack for turning messy web data into structured, testable outputs.
9 years of coding experience
3 years of employment as a software developer
The Blake School
Bachelor of Arts - BA, Computer Science, Bachelor of Arts - BA, Computer Science at Northwestern University
A collaborative documentation site, powered by Google Docs.
Role in this project:
Back-end Developer
Contributions:20 commits, 4 PRs, 6 comments in 10 months
Contributions summary:Maxine primarily contributed to the backend logic of the application. They focused on user authentication and authorization, implementing domain-based access control and integrating with Google authentication. Additionally, the user addressed code quality by fixing linting errors and preserved deep links from Google Docs, indicating involvement in content formatting and URL parsing. They also improved site access options by adding per-email access.
Scrape, standardize and share public meetings from local government websites
Role in this project:
Back-end Developer
Contributions:10 commits, 1 PR, 2 comments in 1 month
Contributions summary:Maxine primarily worked on implementing a web scraper using Python and the Scrapy framework, as evidenced by the commit messages and code changes. They added initial scraping logic, cleaned up the scraped data by removing HTML tags and line breaks and added functions to parse specific data points. Furthermore, the user integrated a data source (Chicago Public Library database), showing their focus on extracting and structuring data for the project. Testing was incorporated as well to make sure all aspects of the scraping functionality were working.
scrapeweb-scrapingpythonopen-datascrapy
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