Analyst - Ontology / Knowledge Graphs - 100% Remote || 6-12 Months

Analyst - Ontology / Knowledge Graphs Location: 100% Remote Duration: 6-12 Months Health Care Domain Preferred Must have 4+ Years of experience Healthcare Experience Preferred We are seeking an Analyst - Ontology / Knowledge Graphs with 4 7 years of experience, preferably in the healthcare industry, to support the design and development of ontology-driven data models and knowledge graphs. This role will focus on building ontology graphs, including entity groups, entities, attributes, cardinalities, relationships, and axioms, to enable structured, reusable, and scalable data foundations for healthcare use cases. The ideal candidate brings hands-on experience with ontology tools and knowledge graph development, with Timbr.ai experience preferred. Familiarity with member, claims, provider, and medical records data is highly desirable. Key Responsibilities • Design, develop, and maintain ontology models and knowledge graphs for healthcare data domains. • Define and manage entity groups, entities, relationships, hierarchies, cardinalities, and axioms. • Translate business requirements and healthcare data concepts into scalable ontology structures. • Collaborate with business, clinical, and technical stakeholders to align ontology design with use cases and data products. • Integrate and harmonize data from multiple healthcare sources, including member, claims, provider, and medical records datasets. • Support metadata management, semantic modeling, taxonomy alignment, and data standardization efforts. • Validate ontology quality, consistency, and usability across downstream analytics and application needs. • Work closely with data engineering and architecture teams to operationalize ontology-based solutions. • Document ontology definitions, modeling decisions, and governance processes. • Contribute to best practices for semantic modeling, knowledge engineering, and data interoperability. Required Qualifications • 4 7 years of experience in data engineering, knowledge engineering, semantic modeling, or related fields. • Experience in the healthcare industry, with strong understanding of healthcare data structures and terminology. • Hands-on experience building or supporting ontology graphs and knowledge graph solutions. • Strong understanding of ontology concepts such as classes/entities, relationships, attributes, cardinalities, inheritance, and axioms. • Experience working with ontology modeling tools or semantic technologies. • Ability to work with complex enterprise data and translate business concepts into formal data models. • Strong communication skills and ability to collaborate across functional and technical teams. Preferred Qualifications • Experience with Timbr.ai. • Familiarity with healthcare datasets such as member enrollment, claims, encounters, provider, and medical records/EHR data. • Knowledge of healthcare data standards or frameworks. • Experience supporting data governance, metadata management, or semantic interoperability initiatives. • Exposure to graph-based technologies, RDF/OWL, or related semantic web standards. Key Skills • Knowledge graphs • Ontology development and semantic modeling • Entity and relationship modeling • Cardinalities and axioms • Healthcare data domain knowledge • Metadata and taxonomy management • Cross-functional collaboration • Timbr.ai and ontology tools divyanshu.bansal@largeton.com