Computational Research Analyst

Princeton University

$76K — $86K *
Education, Government & Non-Profit
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Statistics, or related quantitative discipline and 1+ years of experience.
  • Strong quantitative and programming skills, particularly in Python and QGIS.
  • Willingness to learn GIS software and other necessary tools for the project.
  • Experience in gathering and integrating data from diverse sources.
  • Interest in law, government, or democratic reform.
  • Ability to manage multiple projects effectively and efficiently.
  • Strong collaborative and team-oriented mindset.

Responsibilities

  • Conduct original computational research on ranked-choice voting and U.S. electoral changes.
  • Develop and maintain a comprehensive database of redistricting analyses using census and precinct data.
  • Publish datasets and codebooks for public access to facilitate legal and academic work.
  • Collaborate with partners across various states to enhance research outcomes.

Benefits

  • Health insurance options available.
  • Vacation and leave policies as per university standards.
  • Opportunities for professional development.
  • Access to academic resources and libraries.
Full Job Description
Overview

Profs. Sam Wang and Simon Levin perform research on aggregated decision-making through rule systems. This work includes research into electoral mechanisms including the voting rules, redistricting, and Electoral College. As part of these efforts, they are recruiting a Computational Research Analyst.

The Computational Research Analyst will develop computational analysis of redistricting and voting rules, toward the goal of performing analytics and scholarship relevant to identifying the performance characteristics and inefficiencies of complex U.S. election systems. A main focus is translating the dimensionality of aggregated cognitive approaches of large populations of voters to their ballots, with the goal of going from modeling all the way to practical interpretability. The work will be made publicly available through peer-reviewed scientific scholarship as well as databases that may be of use to a variety of audiences.

The work will include dissemination and archival of codebooks, scripts, map content, and analytics. Other work includes the investigation of electoral rules such as ranked-choice voting and other modifications, with the goal of quantifying functional impacts. Translation to general audiences is part of the work and will produce content that is understandable to nontechnical readers (for example see one publication, the Princeton Gerrymandering Project). This comes in addition to other scholarship in scientific, statistical, and law journals.

This position is suitable for someone with graduate or postgraduate level competence in one or more relevant subject areas, including computational simulation, model testing, and geospatial analysis.

The term of this appointment is 1 year, with the possibility of renewal based upon satisfactory performance and funding.

Responsibilities

  • Perform original computationally intensive research on ranked-choice voting and other proposed changes to U.S. electoral institutions.
  • Maintain and expand a high-quality database of computationally driven analysis of redistricting plans for all 50 states combining census data, precinct-level results, and other information using Python (including numpy) and GIS software.
  • Publish codebooks and datasets to allow public access to analysis, and to drive legal and academic scholarship.
  • Coordinate with collaborators in several states.


Qualifications

Essential Qualifications:
  • This position requires a Bachelor's degree in Computer Science, Statistics, or related quantitative discipline and 1+ years of experience.
  • Strong quantitative and programming background (Python, QGIS)
  • A willingness to learn GIS software and other programs or tools necessary for the project
  • Experience gathering and combining data from many disparate sources
  • An interest in law, government, or democratic reform
  • Ability to balance and work on several projects simultaneously and successfully
  • Strong orientation toward teamwork and collaborative research


Preferred Qualifications:
  • Background in high-performance computing (C, C++, or a comparable language) is a plus.
  • Excellent writing and verbal presentation skills are also highly desired.


Standard Weekly Hours

36.25

Eligible for Overtime

No

Benefits Eligible

Yes

Probationary Period

180 days

Essential Services Personnel (see policy for detail)

No

Physical Capacity Exam Required

No

Valid Driver's License Required

No

Experience Level

Associate

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Salary Range

$76,000 to $86,000

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