Patrick Stetz is a data engineer with a decade of technical experience and over four years focused on building scalable, reliable data solutions at LinkedIn. He blends rigorous statistical training and programming chops with a neuroscience-informed perspective, enabling him to harmonize complex multi-site MRI datasets and optimize large-scale processing pipelines. His background spans research engineering at Stanford—where he managed ≈100TB of MRI data and improved pipeline throughput—to full-stack and data roles that required end-to-end system thinking and robust testing. Based in Oakland, he brings a practical, interdisciplinary approach: comfortable writing production code and deploying on clusters while also translating domain-specific research needs into reproducible data products.
10 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Physics, Bachelor's degree, Physics at University of California, Berkeley
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