Senior Metadata and Standards Specialist

NYU Grossman School of Medicine is one of the nation's top‑ranked medical schools. For 175 years, NYU Grossman School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health, the Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care.

At NYU Langone Health, equity and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace inclusion and individual skills, ideas, and knowledge.

We have an exciting opportunity to join our team as a Senior Data Science Analyst/Engineer.

As part of the Complement‑ARIE program, the NYU‑Sage New Approach Methodologies (NAMs) Data Hub and Coordinating Center will create a controlled access platform for researchers to share and analyze data from NAMs approaches. The program will build tools to standardize and harmonize NAMs data, store it securely, and provide researchers with powerful analytical and visualization tools.

The successful candidate will co‑lead the design and implementation of a comprehensive metadata framework ensuring FAIR (Findable, Accessible, Interoperable, Reusable) compliance and data discoverability across the NAMs Data Hub. This position will extend the C2M2 (Crosscut Metadata Model) to create an integrated framework for NAMs data, develop Common Data Elements (CDEs), integrate terminologies and ontologies for NAMs representation, embed provenance tracking, and author and maintain metadata schemas defining data structures and validation rules to ensure interoperability across all NAMs datasets.

• Design and implement FAIR and interoperable metadata framework for NAMs data
• Define and maintain metadata schemas, profiles, and validation rules for NAMs data modalities such as clinical, omics, imaging, experimental and observational data
• Integrate provenance models (e.g., PROV‑O) into the metadata framework
• Develop comprehensive metadata dictionaries
• Oversee metadata versioning, change management, and deprecation processes, ensuring release notes, impact assessments, and backwardcompatibility
• Establish metadata quality assessment frameworks
• Ensure metadata standards and implementations align with institutional and external policies including privacy, access control, and data use conditions

• Select and integrate appropriate reference terminologies and ontologies for NAMs data representation into a comprehensive NAMs ontology framework
• Perform gap analysis and define mappings and crosswalks between local terminologies and reference ontologies
• Design semantic models using RDF/OWL, SKOS, JSON‑LD, and related standards to enable machine‑interpretable, ontology‑driven data integration and reasoning
• In collaboration with the engineering team, integrate NAMs terminologies and ontologies with existing Standardized Vocabularies and align Metadata schemas with an evolving CDM

• Collaborate with data engineering and analytics teams to integrate metadata and ontology services into NAMs Hub pipelines and analytical platforms
• Participate in the adoption of emerging AI‑enabled tools for metadata extraction, enrichment, and quality assurance
• Use AI‑assisted coding tools to accelerate development of schemas, validation scripts, and queries

• Develop and deliver training and guidance materials on metadata, ontologies, and FAIR data for internal teams and external collaborators
• Coordinate multi‑institutional metadata and standards activities, including consensus‑building, review cycles, and formal approval processes
• Participate in the Standardization Workgroup to develop and refine standards
• Collaborate with related data standard organizations such as CFDE and OHDSI to align NAMs metadata standards with their data models and standardized vocabularies.