Summary
Jonathan Ohayon is a data scientist with 11 years of experience who specializes in turning ML research into production-ready systems, currently architecting hybrid deep learning models for credit risk and fraud detection in Tel Aviv. He has led MLOps and real-time telemetry projects at AWS, cutting deployment times and ensuring high-availability monitoring for TB-scale data, and improved inference latency by 40% through quantization and custom pipelines. His background spans operational analytics in transportation and hands-on leadership from service in an elite IDF reconnaissance platoon, a combination that informs his focus on robust, production-grade tooling and automated retraining for concept drift. Comfortable across the stack—from feature engineering and CI/CD to containerized deployments—he also brings low-level security and C development sensibilities from his security-researcher GitHub persona.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Applied Science - BASc, Computer Science, Bachelor of Applied Science - BASc, Computer Science at The Open University of Israel