Data Analyst - Physical Therapy & Rehabilitation Science

The Data Analyst will primarily clean, maintain, analyze, publish, and develop reports for incoming national data from several methods of assessment including surveys and other measures of human performance. The Data Analyst will develop, analyze, and maintain national benchmarks for over 150 academic healthcare training Institutions nationwide.

Position Responsibilities:

• Use high end algorithms to clean, maintain, analyze, and generate reports for incoming national data from the physical therapy graduation questionnaire (PT-GQ), physical therapy assistant graduation questionnaire (PTA-GQ), and the clinical performance instrument (CPI) generated from a multi-centered nationwide educational project.

• Integrate the use of artificial intelligence algorithms to forecast national trends related to the educational metrics.

• Using high end analytics, develop an annual report with graphics and esthetics for each participating institution.

• Develop and maintain the national educational benchmarks using the PT-GQ and PTA-GQ and embed them within the annual reports so that participating academic healthcare centers may compare their institutions data to the national averages of all participating schools (>150 and growing).

• Manage and upgrade a Web-based Portal (PT-GQ Website) to enable participating institutions to register, upload dates for survey delivery, and receive their annual reports online.

• Maintain effective working relationships with faculty, staff, students, and the public.

• Perform other duties related to data analysis as assigned.

Percent of Time: 100%

Type of Position: Specified Term/One Year

P&S Pay Grade: 3B Professional and Scientific Pay Structure B | University Human Resources - The University of Iowa (uiowa.edu)

Benefits Highlights:

• Regular salaried position located in Iowa City, Iowa

• Fringe benefit package including paid vacation; sick leave; health, dental, life and disability insurance options; and generous employer contributions into retirement plans

• For more information about Why Iowa?, click here

Required Qualifications

• A degree in engineering and a master's degree in data science/analytics or equivalent combination
  of education and experience is required.

• Must be proficient in hardware, software, and data analytical techniques as related to educational
  metrics.

• Excellent capacity to communicate both verbally and in writing the complex algorithm processes to
  enhance understanding among academic leaders nationwide.

• Demonstrated understanding of educational metrics as they relate to learner preparedness, career
  regret, exhaustion, empathy, tolerance for uncertainty, and didactic competencies.

• Demonstrated capacity to analyze complex relationships among educational metrics associated
  with career regret, exhaustion, empathy, tolerance, and educational debt.

• Demonstrated ability to develop the best predictors of educational success using mathematical
  models including high end classification and regression tree analysis and artificial intelligence
  algorithms.

• Demonstrated ability to embed educational lecture videos, and scientific publications into an AI
  based course to provide learner support for the academic mission.

• Demonstrated familiarity with tools like the Clinical Performance Instrument (CPI) used to assess
  competency for clinical practice.

Desired Qualifications

• At least one year of experience specifically working with a multi-centered academic educational
  database from the AAMC or like organization.

• Experience with the PT-GQ benchmarking system.

• PhD in Data Science with evidence of publications/presentations of educational research.

• Experience in trademarking new developments in educational research.

• Capacity to automate big data in genomic applications

Application Process: In order to be considered, applicants must upload a cover letter and resume (under submission relevant materials) that clearly address how they meet the listed required and desired qualifications of this position.

Job openings are posted for a minimum of 14 calendar days. This job may be removed from posting and filled any time after the minimum posting period has ended. Successful candidates will be required to self-disclose any conviction history and will be subject to a criminal background check and credential/education verification. For questions, contact Anne Beyerink at anne-phillips@uiowa.edu.

This position is not eligible for University sponsorship for employment authorization.

• Classification Title: Data Analyst
• Appointment Type: Professional and Scientific
• Schedule: Full-time

• Pay Level: 3B

• Organization: Healthcare
• Contact Name: Anne Beyerink
• Contact Email: anne-phillips@uiowa.edu