[Hiring] Clinical Annotator @Saama Technologies Inc

Role Description

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).

Key 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.

Qualifications

• 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.

Requirements

• 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.

Work Environment

This job operates in a professional office environment. This role routinely uses standard office equipment, including but not limited to, computers, phones, and photocopiers.

Physical Demands

This position requires the frequent and repetitive use of a computer, keyboard, and mouse. Hand and finger dexterity is required.

Other Duties

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

EEO

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. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.