Predoc Research Scientist: Economics & Finance

Princeton University; Princeton (NJ); On-site; USD 58,000 - 75,000; Full time

Benefits offered by this job

In-person role

Access to seminars

Job summary

Princeton University in Princeton, NJ, is hiring predoctoral research specialists to assist multiple economics and finance faculty at the Julis-Rabinowitz Center for Public Policy & Finance. The role focuses on data cleaning, empirical analyses, and advanced modeling to support doctoral study preparation.

The ideal candidate will have a strong quantitative background, coding experience, and the ability to work independently.

Qualifications

• BA/BS in economics, mathematics, or computer science or related field with coursework in economics/statistics/programming.
• Experience with statistical programming in STATA, Python, or R.
• Demonstrated interest in empirical social science.
• Strong analytical, empirical, and writing skills demonstrated through independent work.
• Ability to manage multiple projects and work both independently and in a team.

Responsibilities

• Clean, synthesize, and analyze data; produce empirical analyses and advanced models (machine learning, neural nets, LLMs).
• Prepare results and design figures for reports and presentations.
• Manage data using Python, R, MATLAB, STATA.
• Collaborate with faculty, students, and co-authors; coordinate with JRCPPF team.
• Independently manage timelines and deliverables; make decisions on research progression.

Skills

Statistical programming

Independent problem solving

Scientific writing

Project management

Machine learning awareness

LaTeX/Unix/Linux familiarity

Education

BA/BS in economics, mathematics, or computer science

Tools

STATA

Python

R

MATLAB

Julia

LaTeX

Unix/Linux

Job description

Princeton University in Princeton, NJ, is hiring predoctoral research specialists to assist multiple economics and finance faculty at the Julis-Rabinowitz Center for Public Policy & Finance. The role focuses on data cleaning, empirical analyses, and advanced modeling to support doctoral study preparation.

The ideal candidate will have a strong quantitative background, coding experience, and the ability to work independently.