Ryan Deak
Senior Vice President at Channel Factory
Los Angeles Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolRyan Deak is a seasoned data science and machine learning leader with 13 years of experience building production ML systems and leading analytics organizations, now serving as Senior Vice President in the Los Angeles area. He progressed from hands-on engineering roles at eHarmony to senior leadership at Zefr, scaling data science teams and delivering revenue-impacting optimization and ad-tech solutions. A practical researcher with an M.S. in Artificial Intelligence from UCLA and a background in math and CS, he complements strategy with deep technical chops—evident in contributions to Vowpal Wabbit’s Java backend and JNI integration. Ryan also publishes and maintains open-source projects on GitHub and a personal technical site, reflecting a continuing focus on optimization, program synthesis, and applied machine learning.
13 years of coding experience
17 years of employment as a software developer
BA Mathematics Computer Science, BA Mathematics Computer Science at Vassar CollegeEngineering Mathematics Computer Science, Engineering Mathematics Computer Science at Dartmouth CollegeUniversity of California, Los Angeles
Github Skills (10)
javas10
jna10
java10
cprogramming-language9
c-language9
unit-testing9
machine-learning8
elearning7
cpp6
active-learning6
Programming languages (5)
Github contributions (5)
VowpalWabbit/vowpal_wabbit
Jun 2015 - Jul 2017
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Role in this project:
Backend Developer
Backend DeveloperContributions:14 commits, 3 PRs, 115 comments in 2 years 1 month
Contributions summary:Ryan primarily contributed to the Java backend code of the Vowpal Wabbit project. Their work included updating build scripts for OS compatibility and dependency management, modifying and improving unit tests, and refactoring Java code by removing extraneous imports. Furthermore, the user introduced JNI functionality through changes in Java and C++ code, which indicates a deeper understanding of integrating the Java layer with native code. These contributions improve build processes and facilitate better integration and testing of the VW codebase.
machine-learningvowpal-wabbitc-plus-plusonline-learningcontextual-bandits
deaktator/deaktator.github.io
Aug 2015 - May 2026
Contributions:99 pushes in 10 years 11 months
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