Saama is seeking a Clinical Annotator to serve as a Clinical Subject Matter Expert & Data Abstractor. You will lead clinical pre-annotation validation and data abstraction, bridging raw clinical documentation with high-quality structured datasets for studies in neurology, focusing on Intracerebral Hemorrhage (ICH) and new-onset seizures.

What You'll Do

Perform deep-dive reviews of clinical notes for cohorts of up to 150 patients with Intracerebral Hemorrhage (ICH) and 150 patients with new-onset seizures.
Assess and extract up to 18 specific data elements (5–9 per outcome) across patient groups as defined by client protocols.
Accurately enter abstraction findings into patient-specific datasets and ensure timely delivery of high-quality data.
Perform rigorous human validation on pre-annotated data generated by commercial NLP models (e.g., Amazon Comprehend Medical) or internal LLM tools.
Contribute to the iterative improvement of annotation guidelines to enhance inter-annotator agreement and resolve disagreements between model outputs and human validation.
Partner with Data Science and NLP teams to provide feedback on model performance and assist in the creation of 'golden datasets' for model evaluation.
Maintain strict adherence to HIPAA, data privacy, and security protocols regarding sensitive US patient data.

What We're Looking For

Bachelor’s or Master’s degree in a Healthcare/Life Sciences field (e.g., Nursing/RN, BAMS, BHMS, Pharmacy, or Clinical Research).
Proven experience in Clinical Data Abstraction or medical record review.
Strong ability to interpret unstructured US clinical documentation (Discharge Summaries, Physician Progress Notes, Imaging Reports).
Solid understanding of NLP concepts and experience with data annotation tools (e.g., Label Studio, Prodigy, Inception).
Exceptional accuracy in identifying minute clinical data elements across 100+ page patient files.

Nice to Have

Prior experience within the John Snow Labs (JSL) ecosystem, specifically Health AI Lab and GenAI tools.
Specific experience in Neurology (Stroke/ICH/Seizures) or Oncology (ECOG/Karnofsky scores).
Experience with Named Entity Recognition (NER), Relationship Extraction, and Assertion Status.
Familiarity with incremental batch training and machine learning lifecycles.

Technical Stack

Amazon Comprehend Medical
Label Studio
Prodigy
Inception

Team & Environment

This role involves cross-functional collaboration with Data Science and NLP teams.

Work Mode

This is a remote position.

Saama provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.