Summary
Matthew Lichti is a data scientist with an electrical engineering foundation and over a decade of experience applying machine learning to real-world business problems. He has a strong Python-based toolkit (Pandas, Scikit-Learn, NLP) and hands-on experience building data pipelines and scalable models using PostgreSQL, AWS, Spark, and MapReduce. Matthew has repeatedly focused on customer behavior—predicting churn, identifying high-value segments, and surfacing purchase propensity—for small and mid-sized companies as well as nonprofit work analyzing microfinance loans. His background as a patent examiner and global volunteer who taught tech skills gives him a rare blend of analytical rigor, clear technical communication, and cross-cultural empathy. Based in San Francisco, he’s pragmatic about deploying models into production and curious about Bayesian and bandit methods for better experimentation. He’s actively looking for opportunities to turn messy data into actionable insights that drive measurable outcomes.
11 years of coding experience
10 years of employment as a software developer
Galvanize Data Science
Bachelor’s Degree, Electrical Engineering, Bachelor’s Degree, Electrical Engineering at Iowa State University
Data Science, Data Science at General Assembly
International/Global Studies, Business, International/Global Studies, Business at University of Wales, Swansea
Spanish, Chinese