Summary
Jeremiah Maller is a data scientist and analyst with nine years of experience applying Python, R, and SQL to build predictive models, automate ETL pipelines, and drive causal insights for product and marketing decisions at Apple and the University of San Francisco. Grounded in an MS in Economics and a background in public policy and field research, he blends rigorous experimental design and causal inference with scalable data engineering on platforms like Hadoop, Spark, Snowflake, and BigQuery. He has led large-scale investigations to optimize user engagement and sales, presented actionable analyses to cross-functional stakeholders, and improved reporting through user-level instrumentation and automation. Jeremiah’s experience coordinating 40+ field data collectors in international research and increasing nonprofit fundraising by 65% reveals a rare combination of technical depth, operational leadership, and mission-driven problem solving. Based in San Francisco, he is actively pursuing roles that leverage experimentation, machine learning, and analytics to influence product and policy outcomes.
9 years of coding experience
2 years of employment as a software developer
Trailhead by Salesforce
M.S. Economics Economics, M.S. Economics Economics at University of San Francisco
Computer Science, Computer Science at City College of San Francisco
Bachelor of Arts (BA) Political Science, Bachelor of Arts (BA) Political Science at Macalester College
Spanish, English