Academic Technology Specialist (Quantitative Specialist)

Posted to IASSIST on: 2013-07-18

Employer: New York University Libraries

Employer URL:


New York University’s (NYU) Data Services, a joint ITS and Library facility, is seeking a full-time Academic Technology Specialist to provide quantitative research computing and data support to faculty, students, and staff at NYU. The incumbent will be working in a vibrant and collaborative environment on a team that supports all phases of the data lifecycle in research, teaching and learning including collection, analysis and preservation.

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  •  Provide statistical programming and data analysis support to academic researchers. 
  • Develop and deliver training sessions on research software packages and tools. 
  • Keep up-to-date on the technical and methodological advances in the computational sciences.
  • Supervise a diverse team of graduate student consultants.
  • Perform various administrative duties associated with managing an academic facility.

Required Education:

 Bachelor’s degree in Statistics, Sociology, Economics, Psychology, Mathematics, Political Science or related quantitative-focused field.


Preferred Education:

 Master’s degree (or higher) in Statistics, Sociology, Economics, Psychology, Mathematics, Political Science or related quantitative-focused field.


Required Experience:

  • 3 years related experience, or equivalent.
  • 1-3 years conducting quantitative academic research with at least one of the following statistical software packages: Stata, R, MATLAB, SAS and SPSS. 
  • Proficiency with commonly used statistical and data-oriented methods, including: data cleaning, t-tests, ANOVA, linear regression and generalized linear models. 
  • Excellent public service, communication, organizational and interpersonal skills.

Preferred Experience:

  •  Experience teaching quantitative software packages and/or research methods.
  • Familiarity with a variety of statistical methods, such as: factor analysis, time series analysis, panel data analysis, multi-level modeling, structural equation modeling and classification methods.
  • Knowledge of computer science concepts including data structures and algorithms; experience programming with a high-level language like Python, Julia or C++.
  •  Basic understanding of geographic information systems (GIS), qualitative data analysis and survey research methods.
  • Experience submitting batch jobs on high performance computing systems a plus.

Note: Applicants must be eligible to work in the United States without requiring sponsorship.

Archived on: 2013-08-31