Summary
Nick Gondek is a Data Scientist and Research Software Engineer based in Berkeley with a decade of experience building analytics, ML, and cloud-enabled pipelines for environmental science, agriculture, and policy. He combines time-series, causal inference, and deep learning expertise with hands-on engineering—Python/R, SQL, PySpark/Dask, and AWS/GCP—to turn messy sensor, genomic, and regulatory data into production-ready tools and dashboards. Nick has led cross-functional teams to deploy models for vertical farming variety evaluation and image-based crop phenotyping, and he built an LLM-driven regulatory API to accelerate clean energy siting decisions. His background in ecology and physics (particle theory interests noted in his GitHub bio) gives him a rare ability to bridge rigorous experimental design with scalable software systems. Colleagues rely on him as a technical generalist who cleanup data, ship reproducible workflows, and translate domain complexity into actionable product features.
10 years of coding experience
6 years of employment as a software developer
Bachelor's of Science, Dual Major in (1) Fisheries, Wildlife Conservation Biology and (2) Env. Sciences, Policy and Mgmt, Bachelor's of Science, Dual Major in (1) Fisheries, Wildlife Conservation Biology and (2) Env. Sciences, Policy and Mgmt at University of Minnesota
Masters of Science in Computational Analysis of Public Policy, Emphasis in Statistics and Computer Science, Masters of Science in Computational Analysis of Public Policy, Emphasis in Statistics and Computer Science at University of Chicago