Summary
Paul Schimek is a Principal Data Analyst with nine years of experience translating complex urban and transportation datasets into actionable policy and operational recommendations. He combines rigorous academic training in urban planning (PhD/MAs) with hands-on data science skills—time series, clustering, NLP, and ML—applied to transit performance, bicycle safety, voting behavior, and travel fuel use. At Cambridge Mobile Telematics and his consultancy Effective Data Associates he has turned APC, crash, and election data into concrete schedule, routing, and safety interventions and published analyses that influenced public discussion. Known for clear communication across technical and nontechnical audiences, he builds dashboards and indicators that drive decision-making rather than just reports. An unusual strength is blending deep domain expertise in regional mobility and elections with modern data engineering and statistical methods to reveal nonobvious patterns and policy levers.
9 years of coding experience
3 years of employment as a software developer
Certificate, Data Analytics, Certificate, Data Analytics at Level Education from Northeastern University
Doctor of Philosophy - PhD, City/Urban, Community and Regional Planning, Doctor of Philosophy - PhD, City/Urban, Community and Regional Planning at Massachusetts Institute of Technology
University of California, Los Angeles
Data Science Immersive, Data Science, Data Science Immersive, Data Science at General Assembly
Bachelor of Arts - BA, HISTORY, Bachelor of Arts - BA, HISTORY at Columbia University