Professional Specialist - Research on Policing Reform and Accountability (RoPRA)
Research on Policing Reform and Accountability (RoPRA), a policing research lab co-founded by faculty from Princeton University and the University of Pennsylvania, invites applications for the position of Professional Specialist. The position is for a one-year term, with the possibility of renewal, contingent on satisfactory performance. Rank and salary will be determined on the basis of experience and accomplishments. Reporting to RoPRA faculty, the professional specialist will work with affiliates, students, and external collaborators to provide timely managerial and data support for research projects. The successful candidate will seek out, construct and manage datasets from a wide array of sources, help develop collaborations with law enforcement agencies, and help organize research projects so they progress in a timely manner. In addition, the successful candidate should be able to write summaries of research, perform literature searches and reviews, post and scrape information from the internet, and assist with research design and development. The candidate will also help to create and maintain replication and public datasets on the RoPRA website. QUALIFICATIONS ESSENTIAL QUALIFICATIONS: Excellent research and writing skills Proficiency in statistics and econometrics Strong background in quantitative, experimental research and statistical methods Knowledge of statistical packages including R and/or Python Experience/comfort contacting human sources on the phone to seek data and develop research collaborations Knowledge of standard internet tools and HTML Work experience or subject matter expertise in law enforcement, police oversight, and/or criminal justice a plus Familiarity with specialized software and tools, such as ArcGIS, LaTeX, and GitHub a plus Familiarity with standard political science, economics and/or sociology data sources and analyses a plus EDUCATION REQUIRED: Master's degree in a discipline such as business, computer science, economics, politics, or statistics. Ph.D. preferred The successful candidate must be well-organized, attentive to detail, and able to respond to deadlines in a timely manner. This position is subject to the University's background check policy. TO APPLY Submit a cover letter, resume, transcript, two letters of recommendation and writing sample.