MROQC Health Informatics Sr. Analyst

Women In Science; Ann Arbor (MI); Hybrid; USD 90,000 - 140,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

University of Michigan seeks a data systems specialist to lead the development and optimization of clinical data collection for statewide quality initiatives. You will work on REDCap-based workflows, data validation, and reporting for complex oncology and patient-reported outcomes data.

Responsibilities include partnering with stakeholders, designing technical specifications, and delivering dashboards and portal interfaces to end users. Hybrid onsite work with several days on campus is expected.

Qualifications

• Master's degree in Health Informatics, Data Science, or related field.
• 2+ years experience with large datasets and clinical outcomes data.
• Experience with SAS or Python and Power BI for analysis and visualization.
• Ability to draft statistical tests and interpret results.

Responsibilities

• Lead development and maintenance of clinical data collection systems.
• Design, implement, and optimize data collection workflows (REDCap, etc.).
• Analyze and report complex clinical and patient-reported outcomes data.
• Create dashboards, definitions, and reports for quality improvement.

Skills

Data analysis

Statistical methods

Data visualization

Regression analysis

Survival analysis

Team collaboration

Education

Master's degree in Health Informatics

Master's degree in Data Science

Tools

SAS

Python

Power BI

Relational databases

Job description

University of Michigan

Ann Arbor, MI

Job posting number: #7370304

Posted: September 10, 2026

Application Deadline: Open Until Filled

Job Description

Responsibilities* The Michigan Radiation Oncology Quality Consortium (MROQC) has created a comprehensive clinical data registry of patients receiving radiation treatment for breast, lung, and prostate cancers and bone metastases. The registry is maintained by the University of Michigan (the MROQC Coordinating Center), and it includes both patient-reported outcomes and physician assessments of toxicity as well as data on radiation treatment delivery and dose. Lead the development, implementation, maintenance, and optimization of clinical and health data collection systems, including REDCap-based data collection tools and workflows; support collection, management, validation, and reporting of complex clinical, radiation oncology, and patient-reported outcomes data for statewide quality improvement initiatives; work with stakeholders, team members, and end users to identify and understand MROQC?s end-to-end clinical data collections needs, challenges and opportunities; liaise with stakeholders to define and document MROQC's data collection business needs and technical requirements; develop in-depth understanding of MROQC member hospitals' clinical data collection and reporting processes; lead the conduct of analyses and functional design activities for capturing, loading, storing, and extracting data across MROQC; develop reports and definitions, graphs, dashboards, and portal interfaces; translate stakeholder needs and requirements into detailed technical specification documents to develop and maintain processes and tools for both manual and automated data collections; collaborate with internal teams & external vendors on design, implementation, testing, and deployment of technical data collection specifications; participate in project planning and scope creation, project communications and status reporting; and serve as subject matter expert for clinical registry operations, healthcare data collection systems, and end-user technical support.

Hybrid work arrangement with 3-4 days/week onsite

Required Qualifications

Master's degree in Health Informatics, Data Science, or related + 2 yrs exp working w/large datasets, including administrative claims data, to analyze & interpret clinical outcomes data utilizing SAS or Python & Power BI; programming relational databases, complex data structure, & linkages between data sources; creating data visualizations & reports using SAS, Python, & Power BI; & drafting statistical tests to solve analytic problems, including using descriptive statistics, linear regression, logistic regression, survival analysis, mixed models w/repeated measures, multi-level modeling, & conjoint analysis.