Research Specialist II
Category Research and Laboratory
Full-Time / Part-Time Full-Time
The Department of Sociology at Princeton University seeks applicants for a full-time post-baccalaureate research assistant position in the Eviction Lab. Successful candidates will have a background in statistics, data science, economics, quantitative social science, and/or computer science.
The Eviction Lab at Princeton University is an interdisciplinary and multi-generational research team who has built the first-ever national database of evictions in America. We have validated, mapped, and published our data through an interactive website (evictionlab.org). The Eviction Lab is currently working on a large number of studies on the prevalence, causes, and consequences of housing displacement.
Research assistants will have access to novel and very large datasets not publicly released. In the coming years, the Eviction Lab will begin several new initiatives, including a Joint Statistical Project with the U.S. Census, involving the merging of over 80 million eviction records with several administrative databases and an analysis of the restricted-use file of the American Housing Survey (2017), which will entail the first estimation of informal evictions in national perspective.
We seek self-driven, creative thinkers with strong quantitative skills to assist with research analysis and publication of research findings on housing instability, urban inequality, and public policy. Successful candidates must have previous experience managing and analyzing quantitative data using sophisticated statistical or computer programming techniques. Proficiency in R or Stata is required, previous experience with Python, ArcGIS, web scraping, accessing data through APIs, advanced data visualization, managing large datasets, or working with administrative data is a plus. Previous coursework in sociology, urban studies, or housing instability is not required but useful; an intellectual interest in applying rigorous data analysis to real-world problems is essential.
Salary is competitive and is benefits-eligible. Applicants should submit a dossier including: (1) a complete vita, (2) a cover letter of interest, (3) names and contact information of up to three persons who can serve as references, (4) a writing sample that includes quantitative analysis. All materials should be submitted as 1 continuous pdf. Materials submitted by regular mail or email will not be accepted.
- Data collection, including outreach to courts and municipalities to request data, initiating Freedom of Information Act Requests, and other related tasks.
- Preparing data for use in the Eviction Lab's database or for related Eviction Lab projects. This includes activities like cleaning data in R or Stata, writing code, reformatting files, validating data.
- Tasks related to academic and other publications. These may include library research, collaborating with other Eviction Lab team members on research questions, producing data visualizations, or conducting statistical analyses.
- Attending and contributing to team meetings, collaborating with Eviction Lab undergraduate, graduate, and postdoctoral researchers.
- Attending workshops, conferences and meetings at Princeton and other research organizations.
- Responding to queries from other researchers and members of the public.
- A Bachelor's degree or equivalent and at least one year of related work experience is required.
- Successful candidate must have experience managing and analyzing quantitative data using sophisticated statistical or computer programming techniques, proficiency in R or Stata, ability to apply rigorous data analylsis techniques to real-world problems.
Preferred qualifications include experience Python, ArcGIS, web scraping, accessing data through APIs, advanced data visualization, managing large datasets, or working with administrative data. Previous coursework in sociology, urban studies, or housing instability is not required by useful.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. EEO IS THE LAW