Tyler Kirby
Co-founder, Chief Data Scientist
Missouri, United States
Summary
🤩
Rockstar🎓
Top SchoolTyler Kirby is a data scientist and co-founder with 11 years of experience applying computer vision, Bayesian methods, and NLP to real-world products across startups and enterprise clients. He has built and led data science teams, deployed Bayesian models in production, and designed complex vision pipelines for use cases from logistics optimization to collectibles metric learning. Tyler pairs hands-on engineering—mobile, backend services, and C/C++ realtime vision—with research-driven modeling, and helped scale a 15–20 person practice to deliver faster business impact. His open-source work includes improving Latin syllabification in the Classical Language Toolkit, reflecting a curiosity that spans from ancient languages to modern ML systems. Based in Missouri, he combines founder-level product judgment with deep technical breadth and a track record of shipping robust, tested solutions.
11 years of coding experience
6 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Washington University in St. LouisBachelor's Degree Classics, Bachelor's Degree Classics at New College of Florida
German, Latin, Greek
Stackoverflow
263reputation
22kreached
16answers
0questions
Github Skills (16)
linguistics10
nlp10
python10
historical10
natural-language-processing10
testing10
github8
dom-manipulation6
mongoose6
algorithm6
nodejs6
mongojs6
javascript6
mongodb6
firebase6
Programming languages (4)
Github contributions (5)
cltk/cltk
Dec 2017 - Aug 2019
The Classical Language Toolkit
Role in this project:
Back-end Developer
Back-end DeveloperContributions:34 commits, 26 PRs, 2 pushes in 1 year 8 months
Contributions summary:Tyler primarily focused on improving the Latin syllabifier within the Classical Language Toolkit. Their contributions involved fixing issues related to macrons and the "ui" diphthong, enhancing the accuracy of syllable parsing. They also added unit tests to validate these improvements, ensuring the robustness of the syllabification process. Additionally, the user worked on integrating stop words and Marathi corpus documentation.
nlplingpythonlatinnltk
TylerKirby/auto-commentary
Aug 2020 - Jan 2026
Tools for generating commentaries of Greek and Latin texts
Contributions:1 PR, 61 pushes, 1 branch in 5 years 6 months
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