Senior Metadata and Standards Specialist

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

About the role

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.

Responsibilities

• Design and implement a 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 backward compatibility.
• 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.
• Collaborate with the engineering team to integrate NAMs terminologies and ontologies with existing Standardized Vocabularies and align metadata schemas with an evolving Common Data Model (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.

Requirements

• Master’s degree in a quantitative discipline (Biomedical Informatics, Computer Science, Machine Learning, Applied Statistics, Mathematics, or similar field).
• 5-7 years of experience in machine learning/data science.
• Proficiency in at least one programming language (Python, R) and machine learning tools (scikit-learn, R).
• Knowledge of predictive modeling and machine learning concepts, including design, development, evaluation, deployment, and scaling to large datasets.
• Familiarity with computing models for big data (Hadoop/MapReduce, Spark, etc.).
• Knowledge of databases (Relational/SQL, NoSQL such as MongoDB).

Qualifications

• PhD degree.
• Demonstrated track record of successfully applying metadata and data standards to research or operational datasets in any biomedical field, with tangible outcomes such as improved interoperability, FAIRness assessments, or adoption by external stakeholders.
• Deep knowledge of FAIR principles and their practical application.
• Strong understanding of metadata standards including Dublin Core, DataCite, DCAT, PROV-O, and Schema.org.
• Experience with RDF, SKOS, SPARQL, and semantic web standards for metadata representation.
• Knowledge of controlled vocabularies, taxonomies, and ontologies for metadata annotation.
• Experience with schema definition languages (e.g., LinkML) and validation frameworks.
• Knowledge of and practical experience with biomedical terminologies and ontologies.
• Strong analytical skills for metadata modeling and information architecture.
• Excellent documentation skills with ability to create clear technical specifications and guidelines.
• Strong communication skills for training and stakeholder engagement.
• Demonstrated ability to work collaboratively in multi-institutional research environments.
• Experience with version control systems for managing schemas and documentation.
• Experience with Common Fund Data Ecosystem (CFDE) and the C2M2 metadata model.
• Understanding of biomedical data types including genomics, imaging, and laboratory data.
• Knowledge of OMOP CDM and Standardized Vocabularies.
• Published work on metadata standards or FAIR data implementation.
• Experience coordinating metadata and data standardization initiatives across multiple institutions.
• Experience with automated metadata extraction and enrichment tools.
• Familiarity with AI/ML tools and methods, including their application to metadata enrichment, automated annotation, or standards development workflows.
• Familiarity with NAMs methodologies and alternative testing approaches.

Benefits

NYU Grossman School of Medicine provides a comprehensive benefits and wellness package designed to support employees and their loved ones. Offerings include:

• Financial security benefits.
• A generous time-off program.
• Employee resource groups for peer support.
• Access to a holistic employee wellness program focusing on physical, mental, nutritional, sleep, social, financial, and preventive care well-being.

Pay

The salary range for this role is $121,792.22 - $162,052.80 annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The range does not include bonuses, incentive pay, differential pay, or other forms of compensation or benefits.