Clinical Informatics Analyst - Institute for Genomic Health

Join the Institute for Genomic Health (IGH) at the Icahn School of Medicine at Mount Sinai and play a critical role in advancing precision medicine at one of the nation’s leading academic health systems. As a Clinical Informatics Analyst, you will help enable cutting-edge research in genomic medicine that bridges discovery and patient care. This is a highly collaborative role at the intersection of data science, genomics, and clinical research.

Enable high-impact research: Partner with students and investigators to access, interpret, and analyze large-scale clinical and genomic datasets, accelerating translational discoveries. Build and optimize data infrastructure: Maintain and enhance centralized data resources, documentation, and metadata systems to ensure efficient, scalable, and reproducible research. Drive advanced phenotyping: Develop and implement robust phenotyping algorithms using validated frameworks; harmonize clinical ontologies to support cross-study analyses. Support genomic analyses: Contribute to genetic data quality control and preparation for downstream analyses, including genome-wide association studies (GWAS). Lead and coordinate collaborations: Serve as a key liaison across multidisciplinary teams. Shape research strategy and execution: Contribute to study design, data extraction, statistical analysis, and manuscript development for high-impact publications. Strengthen operational excellence: Support onboarding, contracting, and compliance processes; lead or facilitate project meetings; and develop standard operating procedures to streamline workflows. Innovate with emerging technologies: Evaluate and integrate cutting-edge tools, including AI/LLM-based approaches, to enhance phenotyping and data analysis capabilities. Amplify scientific impact: Contribute to grant proposals, presentations, and dissemination of findings at institutional and national levels.

BA or BS degree required; MS or doctoral degree in Clinical Informatics preferred. 5 years of experience in a related field. Significant expertise with programming and statistical software experience in R, Python, SQL Familiarity with modern database design and operation Familiarity with clinical informatics frameworks and Electronic Health/Medical Record data types and ontologies, including ICD-9/10, LOINC, RxNorm, UMLS, CPT codes, etc. Familiarity with EPIC EHR systems (Clarity, Caboodle) is a strong advantage Strong communication and presentation skills.