Data Analyst II – Medical Informaticist

Location: NYU Grossman School of Medicine; specific work location and work format are not stated.

Salary: $70,481.61–$106,180.20 annually.

Company

hirify.global is an academic medical center focused on medical education, scientific research, direct patient care, and healthcare innovation.

What you will do

• Build and maintain research-ready clinical datasets for observational studies, cohort discovery, computable phenotyping, and real-world evidence generation.
• Extract, transform, and curate Epic, EHR, tumor registry, laboratory, medication, pathology, imaging metadata, and clinical documentation data.
• Map institutional data to OMOP Common Data Model and standard vocabularies, including SNOMED CT, ICD-10-CM, LOINC, CPT, RxNorm, HGNC, and HPO.
• Develop ETL logic, phenotype definitions, cohort rules, metadata specifications, semantic crosswalks, and reproducible data workflows.
• Perform data quality assessment, validation, chart review support, discrepancy analysis, and documentation of transformation logic and results.
• Collaborate with engineers, clinical informaticians, researchers, analysts, data scientists, and operational teams to deliver fit-for-purpose datasets and reports.

Requirements

• Bachelor’s degree in Biomedical Informatics, Health Informatics, Data Science, Biostatistics, Computer Science, Public Health, Epidemiology, or a related field; a master’s degree is preferred.
• At least 3 years of relevant experience with clinical, observational, or research data in a healthcare or related environment.
• Experience with Epic or comparable EHR ecosystems, clinical data warehouses, and research-oriented data extraction and curation.
• Experience supporting cohort identification, phenotyping, registry datasets, chart review, data quality assessment, or observational analytics.
• Experience using Python, R, SQL, and related tools for healthcare data management and reproducible analysis.
• Ability to communicate effectively with all levels of the organization.

Nice to have

• Experience with OMOP Common Data Model, OHDSI tools, or other common clinical research data models.
• Experience using AI coding assistants such as GitHub Copilot, OpenAI Codex, or Claude Code for analytics, ETL, documentation, code review, and quality assurance.

Culture & Benefits

• Inclusive academic medical environment supporting faculty, staff, and students.
• Comprehensive benefits and wellness package for employees and their families.
• Financial security benefits, paid time off, employee resource groups, and retirement support.
• Wellness resources covering physical, mental, nutritional, sleep, social, financial, and preventive care.