Summary
Noah Athens is a Principal Data Scientist based in Oakland with nine years of experience transforming geoscience rigor into production-grade AI/ML solutions for semiconductor and sensing industries. Trained as a geophysicist with a PhD from Stanford, he blends scientific computing, uncertainty quantification, and domain expertise to build robust models for demand forecasting, image-based defect analysis, and sensor-driven field campaigns. At Analog Devices and Maxim Integrated he led teams deploying hierarchical time-series and computer vision pipelines that moved from prototype to operational systems. His background designing novel geophysical hardware and remote data-acquisition platforms gives him an uncommon appreciation for real-world instrumentation constraints and noisy data. Colleagues rely on him to bridge research-grade methods and scalable engineering, especially where physics-informed ML and quantitative uncertainty matter.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BS), Geological & Environmental Sciences, Bachelor of Science (BS), Geological & Environmental Sciences at Stanford University