Summary
Jaren Haber is a Senior Data Scientist and computational social scientist with 10 years of experience translating large-scale text and social data into actionable insights for government, academia, and policy audiences. He leads projects end-to-end—from framing research questions and building capacity to delivering reproducible workflows and open-source code—specializing in NLP, machine learning, and statistical methods applied to digital information flows, inequality, and education policy. At GAO he builds scalable analytics for audits; previously his research at Georgetown and Dartmouth used hundreds of millions of social posts, news articles, and surveys to map misinformation, mortality signals, and education outcomes. A seasoned instructor and community builder, he designs data science courses and practicum projects that partner with external stakeholders, and he contributes to multiple public codebases that prioritize reproducibility. Notably, he has operationalized rapid web-scraping and blended supervised workflows to track fast-moving public-health and misinformation phenomena at scale.
10 years of coding experience
3 years of employment as a software developer
PhD, Sociology, PhD, Sociology at University of California, Berkeley
BA, Socio-cultural Anthropology, BA, Socio-cultural Anthropology at University of California, Davis
Spanish