John Jay College of Criminal Justice
BMW Building, Suite 1140 | West 59th Street
THE NATIONAL NETWORK FOR SAFE COMMUNITIES AT JOHN JAY COLLEGE (NNSC) seeks a part-time or full-time data science intern to support its data-driven action research. The Data Analytics team conducts intensive data analysis to inform the implementation of the NNSC’s crime reduction strategies.
The Data Analytics team is responsible for generating regular data reports in order to illuminate crime trends and aid the innovation of core strategies. In addition, the Data team works with partner jurisdictions to develop data management and analysis protocols that support the implementation of the Network’s ongoing strategies. To that end, NNSC is seeking a data science intern who is comfortable working with messy data and has a willingness to learn our analytical processes. The primary tasks revolve around building, exploring, cleaning, coding, analyzing and/or visualizing datasets. Specific responsibilities will be dependent on the intern’s skillset and will be discussed in detail during the interview process. Ideal candidates will be fluent in R, with preference given to candidates who have experience working with Shiny, building dashboards, and/or conducting text analysis.
Responsibilities may include, but are not limited to:
- Exploring, cleaning, and coding NNSC’s crime data using data science techniques
- Building datasets and analyzing partner crime dynamics building internal-facing and external-facing dashboards (e.g. Shiny)
- Generating tables and data visualizations, particularly those that are interactive
- Preparing data and examining results of social network and geospatial analyses
- Creating and maintaining systems, tools, and processes to track key metrics related to strategy implementation, success, and innovation in the Network sites
- Supporting ongoing strategic operations as needed with additional data management and analysis to address specific challenges and question as they arise
The Data Analytics team requires someone who is a self-starter, can work independently, and has a strong motivation to work with NNSC’s data.
- Familiarity with one or more of the following: R, Python, or Stata
- Preferred: familiarity with one or more of the following R packages: Shiny, flexdashboard, ggplot2, dplyr, plotly, or similar packages
- Familiarity with ArcGIS or similar mapping software preferred, but not required
- Proficiency in Excel is required
- Ability to work with others efficiently and effectively in a fast-paced environment
- Excellent organization skills with ability to prioritize and handle multiple tasks simultaneously and strong orientation to detail
- Strong sense of professionalism and discretion
- Demonstrated interest in and knowledge of criminal justice issues preferred, but not required
- Currently pursuing an undergraduate or graduate degree in data science, computer science, economics, quantitative social sciences, or related field.
The National Network can support interns eligible for federal work-study or seeking to receive college credit for their internship hours. For part-time or full-time interns who do not have funding through an outside source (school, work-study, grant, etc.), a stipend will be available for the term of the internship.
To qualify for federal work-study/college credits: Students are responsible for obtaining advance approval from their institution for both 1) using their internship for college credit and/or 2) receiving federal-work study payments while at the National Network. Please obtain this approval before your interview and be prepared to provide proof of eligibility and/or award.
How To Apply
How to Apply
Visit goo.gl/AfGVxI to apply. Cover letter and resume in a single PDF required. Submitting a sample of work relevant to this position is not required, but may be asked during the interviewing process. Therefore, candidates are encouraged to submit a sample as part of their application.
The preferred deadline to apply by is Sunday, March 25th. A start date as early as May will be considered. Please detail your availability in your cover letter.