Network Analysis Research Scientist, The Center for Policing Equity

Location: New York, New York
The Center for Policing Equity 
Network Analysis Research Scientist

New York, NY
About The Center For Policing Equity
The Center for Policing Equity is a research and action think tank that, through evidence-based approaches to social justice, conducts research and uses data to create levers for social, cultural and policy change. 
Position Description
The Center for Policing Equity is looking for a skilled quantitative researcher with a focus on network analysis as well as a passion for research on race and policing. The Network Analysis Research Scientist will focus primarily on producing high-level scholarship and public reports that leverage aggregated data from the uniquely robust and ever-growing National Justice Database. The National Justice Database is the first and largest database on police behavior in the country (e.g., vehicle stops, pedestrian stops, use of force, complaints against officers, etc.).

Key Responsibilities
  • Conduct advanced quantitative analyses on policing data, and contribute to reports and academic research articles relevant to the intersection of law enforcement and issues of racial and gender equity, with a focus on networked relationships such as officers in a police department and their interactions with individuals in the community, and individuals in community survey samples, including students and their teachers.
  • Help to develop, maintain, and maximize the utility of the nation’s first and largest database of police behavior data
  • PhD/ABD, (exceptional candidates with M.A. or M.S. will also be considered) in a relevant field (e.g., Criminology, Demography, Political Science, Sociology, Epidemiology, Psychology, Data Science), with an interest in social science and law regarding policing and social justice
  • Published research articles focused on policing and/or race
  • Experienced in network analysis/exponential-family random graph models (ERGMs), particularly for multilevel networks; Bayesian data augmentation.
  • Superior research skills; strong quantitative and analytic skills
  • Experience with geocoded data and multi-level modeling (using Stata, SAS, SPSS, R and/or Python)
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