Annotation Quality Lead

Role:

Experience:

Location:

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A Day in the Life

• Oversee quality checks, which involve interdisciplinary and intradisciplinary datasets, as well as randomized assessments to ensure the accuracy and consistency of annotations.

• Perform intra- and inter-annotator quality control measures to detect and correct discrepancies within the annotation workflow.

• Conduct regular audits to ensure compliance with standardized annotation practices.

• Work closely with the Annotation Team to support ongoing quality assurance of annotation infrastructure.

• Assist in creating and maintaining a Gold Standard database with reliable labels for quality benchmarking.

• Conduct randomized checks to ensure annotation quality across the dataset and assess annotation performance.

• Coordinate with the Annotation Program Liaison to review project objectives and quality standards.

• Define appropriate sample sizes and quality control datasets, working directly with scientists and engineers on each study.

• Lead training sessions or competency evaluations to ensure adherence to annotation standards prior to project initiation.

Must Have

• Bachelor’s or Master’s degree in Radiology, Medical Imaging, Pharmacy, Biomedical Engineering, or a related field, statistical background is a plus.

• Expertise in medical imaging modalities (CT, MRI, X-ray, ultrasound) and proficiency with medical annotation tools (e.g., ITK-SNAP, 3D Slicer, Labelbox, V7 Labs).

• Strong understanding of clinical anatomy, pathology, and medical terminology

• Proven experience in medical image annotation, quality assurance with deep familiarity with DICOM, PACS, and other medical imaging systems, or a similar role within data-driven environments.

• Strong analytical skills and meticulous attention to detail.

• Effective communication and collaboration skills for cross-functional teamwork.

• Familiarity with annotation tools and quality control software.

• Knowledge of regulatory requirements, including HIPAA and GDPR compliance, for handling medical data.

Principal Working Relationship

• Reports to AI / Data Science Manager.

• Collaborates closely with annotation specialists, scientists, and engineers across interdisciplinary teams.

Nice to Haves

• Experience with AI-driven medical image analysis models and deep learning techniques.

• Knowledge of automated annotation tools or semi-automated pipelines.

• Familiarity with clinical domains like oncology, cardiology, or pathology is a plus.