Pre-Doctoral Research Specialist — Economic Data & ML

Princeton University; Princeton (NJ); On-site; USD 65,000 - 90,000; Full time

Job summary

Princeton University is seeking several full-time pre-doctoral senior research specialists to advance empirical economics research. The role emphasizes data processing, analysis, survey design, and simulation, serving as rigorous preparation for Ph.D. programs.

You will work with prominent faculty on topics such as income inequality, regional development, and tax policy, gain hands-on modeling experience, and present findings in seminars and reports to support ongoing research projects.

Qualifications

• BA/BS in economics, mathematics, or computer science or related field with strong coursework in economics, math, stats, and programming.
• Experience with statistical programming in STATA, Python, or R.
• Demonstrated interest in empirical social science.
• Excellent analytical, empirical, and writing skills demonstrated through independent work.
• Ability to manage multiple projects independently and in teams; proactive and goal-focused.

Responsibilities

• Clean, synthesize, and analyze data; build empirical analyses and advanced statistical models.
• Prepare results and design figures for reports and presentations.
• Manage data using Python, R, MATLAB, and STATA as requested.
• Collaborate with faculty, students, and external co-authors.
• Independently manage timelines and deliverables for research projects.

Skills

Quantitative background

Coding experience

Independent researcher

Academic writing

Education

BA/BS in economics, mathematics, or computer science

Tools

STATA

Python

R

Job description

Princeton University is seeking several full-time pre-doctoral senior research specialists to advance empirical economics research. The role emphasizes data processing, analysis, survey design, and simulation, serving as rigorous preparation for Ph.D. programs.

You will work with prominent faculty on topics such as income inequality, regional development, and tax policy, gain hands-on modeling experience, and present findings in seminars and reports to support ongoing research projects.