Patrick Cavins is a Staff Technical Writer and former data scientist with nine years of interdisciplinary experience bridging academic research and technical documentation for AI/ML products. He moved from a PhD in chemistry and postdoctoral work—where he led analytics, synthesis, and regulatory-focused tooling—to senior technical writing roles at AWS (SageMaker, Comprehend Medical, Deep* devices) and now SentinelOne, translating complex ML concepts into clear developer-facing content. He’s skilled at building reproducible pipelines and dashboards, with hands-on experience in PCA-driven outlier detection, NMR/LC-MS characterization, and semi-automated lab protocols that reduced risk and improved throughput. Based in Seattle, he pairs domain knowledge in chemistry and biology with practical cloud ML expertise, making him effective at documentation that’s both scientifically rigorous and production-ready. An oft-overlooked strength is his history as an educator and grant organizer, which informs his ability to design learning-first docs and stakeholder-aligned resources.
9 years of coding experience
12 years of employment as a software developer
BA Biochemistry Spanish, BA Biochemistry Spanish at Knox College
The open source version of the AWS DeepLens user guide. You can submit feedback & requests for changes by submitting issues in this repo or by making proposed changes & submitting a pull request.
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Patrick Cavins - Staff Technical Writer at SentinelOne