Scott Koenig is a research-focused data scientist with 11 years of experience translating social science questions into rigorous, policy-relevant analyses. As a Research Associate in New York, he leads teams that convert child welfare settlement targets into quantitative measures, automates preprocessing and analysis with readable, generalizable code, and serves as a statistical resource for colleagues. His background includes designing and running NIH-funded longitudinal studies using RCTs, mixed-effects models, latent profile analysis, and structural equation modeling, and he has a track record of turning technical findings into clear reports and presentations for diverse audiences. He pairs deep methodological training from a PhD in Psychology with practical experience in workforce and education research, and often bridges technical and stakeholder perspectives to drive actionable recommendations. A bilingual neurosciences graduate who has taught abroad, he brings both quantitative rigor and cross-cultural communication skills to multidisciplinary teams.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, PSYCHOLOGY, Doctor of Philosophy - PhD, PSYCHOLOGY at The Graduate Center, City University of New York
Bachelor of Science (B.S.), Neuroscience with Spanish minor, Bachelor of Science (B.S.), Neuroscience with Spanish minor at The Ohio State University
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