Associate Professional Specialist for Princeton Industrial Relations Section-Bleemer Lab

Princeton University; Princeton (NJ); On-site; USD 72,000 - 77,000; Full time

Job summary

Princeton University in Princeton, NJ seeks an Associate Professional Specialist to work on Bleemer Lab research. The role focuses on building a novel database from historical transcripts and applying econometric models to examine higher education policies.

The APS will lead data engineering efforts on encrypted GPU clusters, supervise staff, and contribute to policy briefs and publications, with occasional travel to research sites. The appointment is one-year, with renewal potential.

Qualifications

• Masters degree in Economics, applied Mathematics, Computer Science, Statistics, or related discipline.
• Experience with real-world education data sets is required.
• Graduate-level coding/algorithm skills and proficiency in statistical programming (Stata, R, Python, MATLAB, SAS, LaTeX).
• Proficiency in quantitative text analysis methods (LIWC, LDA) preferred.
• Experience with large language models (Qwen, Dots LLM) is a plus.
• Experience with cluster computing resources and workflows.

Responsibilities

• Employing NLP and ML techniques to construct and categorize transcript records from images and text.
• Geolocating schools/addresses and merging multiple data sources into research databases.
• Applying frontier statistical methods and ML to study admissions and housing policies.
• Supervising undergraduate researchers, data engineers, and staff.
• Producing policy briefs, slides, and academic studies; presenting at lab meetings.
• Assisting with drafting materials for publication and IRB submissions.

Skills

Quantitative text analysis

NLP

Machine learning

GIS

Cluster computing

Written and oral communication

Data analysis

Education

Master's degree in Economics or related field

Tools

Stata

R

Python

MATLAB

SAS

LaTeX

Job description

Associate Professional Specialist for Princeton Industrial Relations Section-Bleemer Lab

Princeton, NJ

Salary Range

$72,000 - $77,000

Description

The Industrial Relations Section (IRS) and the Department of Economics seek a highly motivated and experienced specialist to contribute to the research of Professor Zachary Bleemer during the 2027-2028 academic year. Bleemers research interests focus on American higher education. His recent work examines changes in the college mobility pipeline, meritocratic consensus and stratification, and the impact of college major restrictions in. The appointment will be made at the rank of Associate Professional Specialist (APS).

The APS will contribute towards both the construction of a novel database of 1920-2000 City University of New York student transcripts (employing advanced natural language processing and machine learning techniques). They will then employ those data using a series of econometric and statistical models to investigate the short- and long-run consequences of CUNY's 1970 Open Admissions policy, 1970s fluctuations in state funding support, and 1990s return to selective admissions. They will interpret these findings in context of related frontier scholarship to determine the degree of supermodularity in the return to high-value universities and the value-added return to block grant funding.

Responsibilities include:

• Employing Qwen and Dots LLMs and text analysis tools like LIWC and latent Dirichlet allocation using advanced engineering skills on an encrypted slurm GPU cluster to produce, clean, and categorize computer-readable student transcript records from image and unformatted text files.

• Using GIS software, subject-specific knowledge, and fuzzy-match algorithms to geolocate schools and addresses and merge individual-level student, voter, housing, survey, Census, and tax data into comprehensive research-grade databases.

• Employing frontier statistical techniques -- including recentered instruments and a variety of machine-learning algorithms -- to analyze long-run effects of U.S. university admissions and housing policies.

• Managing undergraduate research assistants, data engineers, and other research staff providing analytical support on related research tasks.

• Producing draft policy briefs, presentation slides, and academic studies and present findings at regular lab meetings.

• Assisting with drafting materials for publication.

• Coordinating and submitting applications for review by Princetons Institutional Review Board.

The work location for this position is primarily in-person on campus at Princeton University with occasional research trips to Italy. This position is subject to the University's background check policy. This is a one-year term position with the potential for renewal for a second term.

This position is not eligible for sponsorship of an H-1B visa requiring consular processing; other visa sponsorships (including H-1B visas not requiring consular processing) may be available, as appropriate.

Qualifications

• Masters degree in Economics, applied Mathematics, Computer Science, Statistics, or related discipline

• Prior research experience in the fields of Economics

• Experience working with real-world data sets, including education or school administrative data

• Graduate-level coding/algorithm skills and proficiency in statistical programming, especially Stata, R, Python, MATLAB, SAS, LaTeX

• Proficiency in quantitative text analysis methods, such as LIWC and latent Dirichlet allocation

• Proficiency in, or experience with, large language models, such as such as Qwen and dots LLM

• Experience with utilizing cluster computing resources and workflows

• Strong written and oral communication skills

• Excellent organizational and time management skills

Equal Opportunity and Pay Transparency

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.

Pay Transparency Disclosure

The University considers factors such as (but not limited to) the 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.

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

Equal employment opportunity, including veterans and individuals with disabilities.

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