Summary
Stephanie Eckman is a research-focused data scientist with 11 years of experience designing and managing high-quality data collection and survey methodology for academic, government, and industry settings. She blends rigorous survey-methods expertise from a Ph.D. in Survey Methodology with practical experience at institutions such as NORC, the World Bank, RTI, and now University of Maryland and Amazon, emphasizing weighting, sampling, and reducing data-collection burden. Known for improving data quality and training robust machine learning inputs, she translates complex causal and panel-data methods into usable research and operational processes. She also has taught advanced methods at the university level and consulted internationally on survey implementation, bringing both pedagogical clarity and field-tested solutions to large-scale measurement challenges.
11 years of coding experience
5 years of employment as a software developer
Bachelor's Degree, Econmics / Mathematics, Bachelor's Degree, Econmics / Mathematics at Smith College
The University of Maryland, College Park
University of Massachusetts Amherst
German, English