Clinical Informatics Analyst - Institute for Genomic Health

Mount Sinai Health SystemNew York, NY

About The Position

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.

Requirements

  • 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.
  • Strong communication and presentation skills.

Nice To Haves

  • Familiarity with EPIC EHR systems (Clarity, Caboodle) is a strong advantage

Responsibilities

  • 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.
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