Summary
Jonathan Grundy is a Senior Data Scientist with a decade of experience applying time series, NLP, and geospatial analytics to urban development, BPO, and financial domains across city agencies, nonprofits, and large consultancies. He blends hands-on Python engineering with production-facing analytics—building anomaly detection for financial time series, wrapping APIs, and processing multi-hundred-million interaction datasets for call-center insights. His work on municipal projects includes spatio-temporal analyses (e.g., snowplow GPS optimization) and practical GIS consulting, showing a talent for turning messy public-sector data into operational decisions. Comfortable both leading teams at firms like Booz Allen and contributing individually in research labs, he thrives on collaborations with public agencies and translating domain expertise into actionable models. A Seattle-based practitioner with an MS in Applied Urban Science and Informatics, he pairs technical depth with a clear eye for policy-relevant impact.
10 years of coding experience
11 years of employment as a software developer
Master of Science (M.S.), Applied Urban Science and Informatics, Master of Science (M.S.), Applied Urban Science and Informatics at NYU Center for Urban Science + Progress
Bachelor of Science (BS), Political Science, Bachelor of Science (BS), Political Science at University of California, Irvine
English