Valerie Martinez is a data scientist with Child Trends’ data science program area who takes special interest in the intersection of child welfare and justice system involvement. She has experience employing advanced statistical methods and machine learning techniques to answer unique research questions, quantitative and qualitative data collection, and data visualization.  

Valerie’s most recent projects have involved independently programming two interactive web applications using R shiny, an extension of the R programming language used to create interactive web-based tools, with the goal of making information available to a broader audience: (1) the Child Care and Early Education Licensing Information Hub for the Office of Planning, Research and Evaluation; and (2) a dashboard for a National Science Foundation-funded project to depict how recommended juvenile justice dispositions change depending on child and community demographics. Valerie has also led quantitative analyses for multiple projects, one of which was recently published in the Children and Youth Services Review. Prior to joining Child trends, Valerie was the project coordinator for two cohorts of the National Institutes of Health’s Environmental Influences on Child Health Outcomes (ECHO) project: the Developmental Impacts of NICU Exposures cohort and the Boricua Youth Study cohort. 

Valerie has a Master of Public Health from NYU’s School of Global Public Health with a concentration in social and behavioral sciences. Her Master’s thesis focused on understanding the protective effects of racial/ethnic identification and exploration on health outcomes in young Hispanic and Black individuals of the LGB community.