Research Specialist II

The Department of Sociology at Princeton University seeks applicants for full-time post-baccalaureate research assistant positions in the Eviction Lab. Successful candidates will have a background in quantitative social science, economics, statistics, data science, and/or computer science.

The Eviction Lab at Princeton University is an interdisciplinary 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 many studies on housing insecurity, homelessness, housing affordability, and more. Research assistants will have access to novel and very large datasets not publicly released, and the opportunity to work closesly with senior researchers.

We seek self-driven, creative thinkers with strong quantitative skills to assist with analysis, data collection, and publication of research findings. Successful candidates must have previous experience managing and analyzing quantitative data using sophisticated statistical or computer programming techniques. Proficiency in R 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 or research experience in sociology, urban studies, or housing instability is not required but useful.

This is a one year term appointment with the possibility of an additional year renewal.

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. You may also submit a coding sample however that is not required. All materials should be submitted as 1 continuous pdf. Materials submitted by regular mail or email will not be accepted.

Responsibilities include:

• 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, writing code, reformatting files, validating data.
• Tasks related to academic and other publications such as 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.

Responding to queries from other researchers and members of the public.

Essential Qualifications:

• Bachelor's degree or equivalent
• 3+ years relevant experience
• Experience managing and analyzing quantitative data using sophisticated statistical or computer programming techniques
• Proficiency in R or Stata
• Ability to apply rigorous data analysis techniques to real-world problems

Preferred Qualifications:

• Python
• ArcGIS
• Web scraping
• Accessing data through APIs
• Advanced data visualization
• Managing large datasets or working with administrative data
• Previous course work in sociology, urban studies, or housing instability

Princeton University is an Equal Opportunity 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.

The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.

If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.

The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.

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