Research Specialist: Data, ML & Econometrics in Economics

Princeton University; Princeton (NJ); On-site; USD 65,000 - 70,000; Full time

Job summary

Princeton University’s Industrial Relations Section seeks an Associate Professional Specialist to contribute to Professor Will Dobbie’s research for 2027–2028. The role centers on developing and managing administrative datasets, building machine learning models, and maintaining a multi-module codebase.

The work is primarily on campus with occasional research trips; this is a one-year term with potential renewal.

Qualifications

• Masters degree in Economics, applied Mathematics, CS, Statistics, or related field.
• Experience with real-world data sets, including education data.
• Graduate coding/algorithm skills; proficiency in Stata, R, Python, MATLAB, SAS, LaTeX.
• Proficiency in quantitative text analysis methods.
• Experience with large language models in research context.
• Strong written and oral communication skills.
• Excellent organizational and time management skills.
• Proficiency in Italian is a plus.

Responsibilities

• Constructing and managing administrative datasets in high-stakes settings.
• Building advanced machine learning models using structured and unstructured data.
• Maintaining a multi-module codebase; working with data models.
• Conducting applied econometrics tasks in Stata or R; generating publication-ready tables and figures.
• Coordinating with third-party contractors and software engineers.
• Producing detailed reports, policy briefs, and presentations for publication.
• Coordinating and submitting IRB review applications.

Skills

Strong written and oral communication

Excellent organizational skills

Time management

Proficiency in Italian (plus)

Graduate coding/algorithm skills

Data handling

Quantitative text analysis

Team collaboration

Education

Masters degree in Economics/related field

Tools

Stata

R

Python

MATLAB

SAS

LaTeX

Large language models

Job description

Princeton University’s Industrial Relations Section seeks an Associate Professional Specialist to contribute to Professor Will Dobbie’s research for 2027–2028. The role centers on developing and managing administrative datasets, building machine learning models, and maintaining a multi-module codebase.

The work is primarily on campus with occasional research trips; this is a one-year term with potential renewal.