Imaging Quality Analyst (Part-Time)

United States·Clevelandmid

OtherHealthcareQuality Analyst

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Overview

About Aegis Ventures Aegis Ventures partners with entrepreneurs and industry leaders to launch and scale transformative companies in digital health and artificial intelligence.

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About the Role

~1 min read

Perform manual visual review of medical imaging studies using approved DICOM viewers
Validate imaging studies against client-specific acceptance criteria, including:

Modality and series accuracy
Anatomical coverage and completeness
Image usability and acquisition artifacts

Confirm required images and series are present and properly structured

Verify that no Protected Health Information (PHI) is present in imaging data prior to delivery, including:

Burned-in text or annotations
Overlays and image corners

Confirm imaging data has been properly de-identified according to Avandra standards
Identify, flag, and escalate suspected PHI exposure or de-identification failures

Document review outcomes using Avandra QA workflows and tools
Apply standardized pass, fail, or needs-review determinations
Maintain clear, auditable records of quality and privacy reviews

Participate in calibration and training sessions to maintain review consistency
Provide feedback to improve automated quality and de-identification checks
Collaborate with Imaging Operations and Engineering teams as needed

Current enrollment in or recent completion of a Radiologic Technology program or equivalent imaging-related training
Familiarity with medical imaging modalities (CT, MR, X-ray)
Ability to navigate and use DICOM viewers (training provided)
Strong attention to detail and ability to follow structured review protocols
Basic technical proficiency with web-based tools and workflows

Attention to Detail: Consistently applies structured review criteria and catches edge cases
Quality & Compliance Mindset: Takes data privacy and quality standards seriously
Reliability & Accountability: Produces accurate, auditable work in a regulated environment
Learning Orientation: Interested in healthcare data, research, and AI/ML applications
Collaboration: Comfortable working with operations and technical teams