Psychometrician - 10921BR

Psychometrician

Department: 
Achievement & Assessment Inst
Location/Division: 
Lawrence
Reg/Temp: 
Regular
Employee Class: 
U-Unclassified Professional Staff

Position Overview

ATLAS is seeking a Psychometrician to support the research and psychometric activities of the Dynamic Learning Maps (DLM) alternate assessment system. Responsibilities include statistical tasks such as cleaning data, managing data sets, and running descriptive and inferential statistics; performing quality assurance checks on analysis and reports; preparing technical documents; presenting to the consortium’s Technical Advisory Committee and other duties as assigned. Experience with Bayesian Networks and/or Cognitive Diagnostic Models preferred.

Job Description

40% - Performs psychometric tasks including item and test analysis, differential item functioning, and standard setting. Uses many types of psychometric models to analyze large-scale assessment data. Produces item analyses and summary data tables for use in technical documentation. Conducts all aspects of operational work related to scoring and reporting including data cleaning, calibration, scoring, quality control, and reporting.

20% - Prepare technical reports and related documents.

15% - Propose detailed research designs and ideas for operational procedures. Conduct research under the supervision of a senior level psychometrician.

15% - Other duties to support the research and psychometric activities for the project.

10% - Present to various audiences, including consortium state education agency partners, Technical Advisory Committees, and professional conferences.

Required Qualifications

  1. Doctoral degree in educational measurement, psychometrics, or other closely related field
  2. Experience with quantitative analysis in more than one statistical application (e.g., SPSS, SAS, R), including experience writing scripts for analysis as evidenced in application materials and interview
  3. Basic knowledge of models that utilize skill networks (graphical models such as Bayes Nets, or psychometric models such as Cognitive Diagnostic Models) as evidenced in application materials
  4. Effective oral and written communication skills for technical audiences, as evidenced in written application materials and interview
  5. Experience managing multiple priorities and deadlines, including adapting in response to changes in work priorities and processes, as evidenced in application materials
  6. Detail oriented with strong organizational skills, as evidenced in application materials and interview

Preferred Qualifications

  1. One or more years of project experience with models that utilize skill networks (graphical models such as Bayesian Networks or psychometric models such as Cognitive Diagnostic Models)
  2. Experience writing technical reports including results of quantitative analyses
  3. Experience with an operational assessment program (e.g., state large-scale or district-level assessments)
  4. Extensive experience writing scripts in R as evidenced in application materials and interview (e.g., building packages, vignettes, etc.)
  5. Experience communicating quantitative information to non-technical audiences
  6. Strong problem solving skills as evidenced by application materials and interview

Additional Candidate Instructions

A complete application includes online application, vita, cover letter highlighting qualifications and including specific examples of experience, contact information for four professional references, and technical writing sample. Only complete applications will be considered.

Application review begins February 19, 2018, and continues until the position is filled.

Contact Information to Applicants

Victoria King
kingv@ku.edu

Advertised Salary Range

Minimum $57,060; Commensurate with experience

Application Review Begins

19-Feb-2018

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Posting Information
Posting ID:
10921BR
Department:
Achievement & Assessment Inst
Location/Division:
Lawrence
Reg/Temp:
Regular
Employee Class:
U-Unclassified Professional Staff
Application Review Begins:
19-Feb-2018
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