Nathan Artz is a staff software engineer and machine learning leader with 11+ years building metrics-driven, production ML and distributed systems that tie closely to business impact. He has led teams and technical strategy at enterprises and startups alike—most recently transitioning with VMware’s EUC business into Omnissa after the Broadcom merger—and previously served as CTO and founder driving product and analytics roadmaps. His strengths span probability, statistics, optimization, and low-latency systems, evidenced by work on sub-10ms real-time ML services and high-throughput analytics for millions of users. Comfortable both in hands-on engineering and cross-functional leadership, he focuses on customer-near solutions that move metrics, not just models. Trained at MIT in computer science and engineering, he blends quantitative rigor with practical delivery across cloud, backend, and data-intensive systems.
11 years of coding experience
13 years of employment as a software developer
B.S. Computer Science and Computer Engineering, B.S. Computer Science and Computer Engineering at Massachusetts Institute of Technology
ARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy.
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