Lead Clinical Science Informaticist

What you'll do

• Create and curate clinical value sets using industry-standard terminologies like SNOMED CT.
• Develop annotation guidelines and ensure their understanding by teams involved in AI projects.
• Define data requirements for AI/ML applications to maintain high data quality standards.
• Implement quality control processes to validate annotated data’s integrity and reliability.
• Lead review cycles of model predictions, providing feedback to improve labeling accuracy.
• Oversee the collection and preprocessing of diverse healthcare datasets for analysis.
• Design performance metrics and ground truth algorithms to evaluate AI/ML models.

What we're looking for

• Proven clinical informatics experience with EHR systems and data.
• Expertise in machine learning, natural language processing, and AI within healthcare.
• Strong background in statistical methods and medical standards/ontologies.
• Proficiency in data preprocessing, feature engineering for AI/ML applications.
• Experience defining data requirements and validating annotated data for AI solutions.
• Familiarity with clinical terminologies (SNOMED CT, ICD, CPT) in data science models.
• Advanced knowledge of healthcare data standards like FHIR Resources and QDM Categories.