Data Annotator

Key Responsibilities:

• Annotate oncology-related clinical documents (e.g., EHRs, pathology reports, radiology images/reports) with high accuracy.
• Label data elements such as cancer types, staging (TNM), biomarkers, treatment regimens, and outcomes.
• Ensure compliance with annotation guidelines, medical ontologies (e.g., SNOMED CT, ICD-O, NCIT), and study protocols.
• Collaborate with oncologists, data scientists, and engineers to improve annotation quality and consistency.
• Participate in quality control and peer review of annotations.
• Maintain documentation of annotation processes and contribute to the refinement of annotation guidelines.
• Support the development and evaluation of NLP and machine learning models by providing clean, structured annotated datasets.

Requirements:

Must-Have:

• Bachelor's degree in life sciences, nursing, medicine, pharmacy, or related field.
• Strong understanding of oncology terminology, cancer biology, and clinical workflows.
• Experience working with clinical data, preferably in oncology.
• High attention to detail and consistency in data labeling tasks.
• Familiarity with EHR systems and clinical documentation.

Preferred Qualifications:

• Advanced degree (MS, MPH, PharmD, RN, MD) with oncology specialization or experience.
• Experience using medical coding systems (ICD-10, SNOMED, MedDRA, NCIT, etc.).
• Prior experience in medical data annotation, clinical research, or biomedical NLP projects.
• Familiarity with tools like Prodigy, Labelbox, Doccano, or custom annotation platforms.
• Understanding of HIPAA and data privacy standards.