Nadia Orfali Hall is a data scientist in the early childhood development research area at Child Trends. Nadia has extensive experience blending her knowledge of early childhood systems with technical abilities. She has over a decade of experience conducting data analysis as well as writing and presenting for both technical and nontechnical audiences. Her recent projects include working on multiple Quality Rating and Improvement System (QRIS) validation studies, creating complex data visualizations, and providing technical assistance to states to help harness their administrative data.
Nadia serves as the project director and quantitative lead on multiple projects, managing day-to-day operations and using both traditional statistical and cutting-edge data science approaches. Her methodological strengths include regression analysis, factor analysis, multiple imputation, experimental, and quasi-experimental design. Her technical skills include Stata, SAS, R, Python, Tableau, GIS, and relational databases. She also serves as the technical administrator for Child Trends’ instance of REDCap, a secure data collection platform, using her understanding of database design and “back-end” programming (e.g., SQL) as well as “front-end” languages (e.g., HTML).
Prior to joining Child Trends, Nadia was awarded a research fellowship at the National Institute of Mental Health, studying emotions and the brain in children with behavioral disorders, such as conduct disorder. Her broad research interests include data science, secondary data analysis, use of administrative data, and spatial analysis.