Clinical Annotator

Saama Technologies Inc

35d • Remote

About The Position

We are seeking a highly skilled and detail-oriented Clinical Subject Matter Expert (SME) to lead clinical pre-annotation validation and data abstraction. This role is critical for our incremental annotation process, focusing on the human validation of NLP-generated data and the precise abstraction of clinical elements from complex medical records. The successful candidate will bridge the gap between raw clinical documentation and high-quality structured datasets, specifically supporting studies in neurology (ICH and Seizures).

Requirements

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

Nice To Haves

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

Responsibilities

• Clinical Data Abstraction: 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.
• Targeted Data Extraction: Assess and extract up to 18 specific data elements (5–9 per outcome) across patient groups as defined by client protocols.
• Dataset Management: Accurately enter abstraction findings into patient-specific datasets and ensure timely delivery of high-quality data to the client. Clinical Annotators to abstract facts from notes and update those in CRFs
• Annotation Validation: Perform rigorous human validation on pre-annotated data generated by commercial NLP models (e.g., Amazon Comprehend Medical) or internal LLM tools.
• Guideline Refinement: Contribute to the iterative improvement of annotation guidelines to enhance inter-annotator agreement and resolve disagreements between model outputs and human validation.
• Cross-functional Collaboration: Partner with Data Science and NLP teams to provide feedback on model performance and assist in the creation of "golden datasets" for model evaluation.
• Compliance: Maintain strict adherence to HIPAA, data privacy, and security protocols regarding sensitive US patient data.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level