Mike Reilly
Senior Data Scientist And Technical Manager
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolMike Reilly is a senior data scientist and technical manager who blends 20 years of urban planning and academic experience with 11 years focused on applied data science for housing, land use, and transportation policy. He builds and scales policy-facing modeling tools—most recently leading enhancements to the Terner Housing Policy Simulator and Bay Area UrbanSim—to translate complex regional economic, demographic, and real estate dynamics into actionable insights for policymakers. Mike has led interdisciplinary teams across government, consulting, and research institutions, delivering large forecasting and feasibility projects for clients like FHWA, SCAG, and Stanford. His work uniquely connects development feasibility modeling with observed development outcomes and travel behavior, bridging microeconomic modeling, spatial analysis, and discrete choice methods. A trained planner with advanced coursework in machine learning and spatial statistics from Stanford and an MIT certificate in applied data science, he combines rigorous academic methods with pragmatic, stakeholder-facing tools. Based in San Francisco, he often pairs deep technical modeling with clear communication to advocates and decision-makers, and maintains an independent consultancy that supports major regional and national clients.
11 years of coding experience
8 years of employment as a software developer
PhD, City and Regional Planning, PhD, City and Regional Planning at University of California, BerkeleyMCP, MCP at UC Berkeley College of Environmental DesignFlintridge Preparatory SchoolAB, Social Science, Japanese Language, AB, Social Science, Japanese Language at UC Berkeley College of Letters & ScienceProfessional Certificate, Applied Data Science, Professional Certificate, Applied Data Science at Massachusetts Institute of TechnologyEarth Institute Fellow, Earth Institute Fellow at Columbia Universitygraduate coursework: machine learning, spatial statistics, geostatistics, multi-agent systems, graduate coursework: machine learning, spatial statistics, geostatistics, multi-agent systems at Stanford University
Japanese
Github Skills (20)
crossword10
simulation10
san10
jstree10
modeling10
data-science9
orientdb9
geoserver7
geography7
geo7
wfs6
gis5
java5
geospatial5
wps5
Programming languages (2)
Github contributions (5)
BayAreaMetro/mapcraft_eg
Aug 2017 - Oct 2019
Contributions:236 pushes, 1 comment, 1 issue in 2 years 3 months
spatialbaysystem-informationbay-area
BayAreaMetro/regional_forecast
Mar 2020 - Sep 2023
Contributions:165 pushes in 3 years 6 months
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