Senior Metadata & Ontology Architect (FAIR Data)

NYU Grossman School of Medicine; New York (NY); On-site; USD 121,792 - 162,053; Full time

Benefits offered by this job

Comprehensive benefits

Wellness program

Job summary

NYU Grossman School of Medicine in New York seeks a Senior Data Science Analyst/Engineer to co-lead the design and implementation of a comprehensive metadata framework for NAMs data, extending the C2M2 model and integrating terminologies and ontologies to ensure interoperability across NAMs datasets.

The role involves collaborating with data engineering and analytics teams, adopting AI-assisted tooling for schema development, and delivering training materials to internal teams and external

Qualifications

• Master's degree in a quantitative discipline and 5-7 years of experience in machine learning/data science.
• Proficiency in at least one programming language (Python, R) and ML tools (scikit-learn, R).
• Knowledge of predictive modeling and ML concepts including design, development, evaluation, deployment and scaling to large datasets.
• Familiarity with Hadoop/MapReduce, Spark; knowledge of Relational/SQL and NoSQL databases such as MongoDB.

Responsibilities

• Design and implement FAIR and interoperable metadata framework for NAMs data.
• Define and maintain metadata schemas, profiles, and validation rules for NAMs data modalities (clinical, omics, imaging, etc).
• Integrate provenance models (e.g., PROV-O) into the metadata framework.
• Develop comprehensive metadata dictionaries and oversee versioning and deprecation processes.

Skills

Machine learning

Data science

Python programming

R programming

Data analysis

Education

Masters degree in quantitative discipline

5-7 years experience in machine learning/ data science

Tools

Python

R

scikit-learn

Hadoop

Spark

SQL

MongoDB

Job description

NYU Grossman School of Medicine in New York seeks a Senior Data Science Analyst/Engineer to co-lead the design and implementation of a comprehensive metadata framework for NAMs data, extending the C2M2 model and integrating terminologies and ontologies to ensure interoperability across NAMs datasets.

The role involves collaborating with data engineering and analytics teams, adopting AI-assisted tooling for schema development, and delivering training materials to internal teams and external