Extra Help - Institutional Research Data Coordinator - College of Medicine

Extra Help - Institutional Research Data Coordinator - College of Medicine

This Position is temporary and limited to 900 hours.

Hiring Department: College of Medicine

Location: Chicago, IL USA

Hours per Week: 37.5

# of Positions: 1

Workplace Type: Hybrid

Posting Close Date: Saturday, June 20, 2026

Salary: The rate of pay for this position is $32.37 per hour.

About the University of Illinois Chicago

UIC is among the nation's preeminent urban public research universities, a Carnegie RU/VH research institution, and the largest university in Chicago. UIC serves over 34,000 students, comprising one of the most diverse student bodies in the nation and is designated as a Minority Serving Institution (MSI), an Asian American and Native American Pacific Islander Serving Institution (AANAPSI) and a Hispanic Serving Institution (HSI). Through its 16 colleges, UIC produces nationally and internationally recognized multidisciplinary academic programs in concert with civic, corporate and community partners worldwide, including a full complement of health sciences colleges. By emphasizing cutting-edge and transformational research along with a commitment to the success of all students, UIC embodies the dynamic, vibrant and engaged urban university. Recent "Best Colleges" rankings published by U.S. News & World Report, found UIC climbed up in its rankings among top public schools in the nation and among all national universities. UIC has over 300,000 alumni, and is one of the largest employers in the city of Chicago.

This position is not eligible for benefits.

Position Summary

Under administrative direction of the Director of Decision Support and the Associate Director of Data Analytics, the coordinator organizes structured data from disparate sources, prepares complex mathematical models and research studies of College of Medicine operations; analyzes/prepares results for publication on the College of Medicine dashboard, a data visualization tool that provides a quick and concise overview of key performance indicators (KPIs) and metrics relevant to the mission of the College.

Duties & Responsibilities

• Directs the formulation of, or formulates, mathematical models (such as Markovian enrollment projections) of College operations (such as clinical productivity, research portfolios, stakeholder census demographics, resource allocation, student flow, enrollment, and academic outcomes).
• Designs and implements statistical computations.
• Prepares or directs the preparation of tables and charts.
• Directs the gathering and analysis of data.
• Interprets data and trends, summarizes results, and prepares reports for submission to university administrators or for publication.
• Directs or performs the coding, testing, debugging, and documentation of mathematical computer programs for developed models (using linear, dynamic and/or stochastic programming techniques).
• Devises, recommends approval, and implements revised methods, procedures, and techniques of section.
• Performs other related duties as assigned.
• Participates the maintenance ETL process and between University EDW and local SQL database.
• Development of procedures providing backend data to various dashboard projects.
• Perform other related duties and participate in special projects as assigned.

Minimum Qualifications

1. Bachelor's degree in computer science, operations research, or other related fields with at least 12 semester hours in computer science and/or mathematical modeling OR Experience and/or training that provided knowledge, skills, and abilities comparable to those normally gained in one of the Bachelor's degree programs listed above
2. One (1) year (12 months) of experience in operations research and/or mathematical modeling

Preferred Qualifications

• Tableau
• SQL w/ MySQL
• Microsoft Office Suite
• Data Structures/Algorithms in C and C++
• Python: NumPy, SciPy, Pandas, Matplotlib, Scikit-learn (Machine Learning), PyTorch (Deep Learning), PyMC (Bayesian Machine Learning)
• Big Data: Dask (Python), PySpark w/ DataBricks