Senior Enterprise Ontologist

GEICO .
For more information, please .Senior Enterprise Ontologist page is loaded## Senior Enterprise Ontologistlocations:
Palo Alto, CA:
New York City, NY:
Richardson, TX:
Dallas, TX:
Chevy Chase, MDtime type:
Full time posted on:
Posted Todayjob requisition :
R0061787
** At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
**** Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.
**** When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge:
Great Company, Great Culture, Great Rewards and Great Careers.
** We are seeking an experienced and innovative Senior Enterprise Ontologist to lead the design and development of enterprise ontologies, knowledge graphs and semantic models tailored for the insurance domain. You will partner closely with cross-functional teams including engineering, product, AI, and various business teams to identify and analyze data sources, develop taxonomies, and create semantic models that enable effective search, retrieval, and analysis of information.

Your expertise in ontology engineering and it’s role in enhancing NLP and AI/ML use cases will be critical in developing cutting-edge solutions that drive innovation, automation and add value to our business. This role will be critical in driving a common understanding and language for the business across all domains. This individual will be part of a team responsible for leveraging semantic platforms and models to accelerate the implementation of context management and agentic AI to address critical business priorities for the data and AI teams.
** Key Responsibilities
*** Design, model, and implement formal ontologies to standardize and integrate diverse insurance data, including unstructured documents (e.g., policy contracts, loss reports) and structured core systems data
* Apply best practices in ontology development and management to improve data understanding, data quality and accessibility.
* Establish governance standards for ontology development, ensuring models evolve with the business, i.e. are extensible and auditable for regulatory reporting.
* Conduct requirement gathering with business stakeholders (e.g. underwriters, actuaries, legal/compliance, claims specialists) to translate complex domain knowledge into scalable semantic models and structures.
* Provide training and guidance to stakeholders on ontology usage and best practices for data organization.
* Conduct ontology mapping and integration from source systems to ontological structures, e.g. knowledge graphs to facilitate data interoperability and integration across systems.
* Collaborate with domain teams to define and document enterprise data models in alignment with defined ontologies
* Evaluate ontologies and knowledge graphs created through automated semantic layer tools to ensure accurate representation of business; facilitate modeling of accurate ontologies in these tools
* Partner with data engineering team to outline vision for convergence of enterprise ontologies, enterprise data models and semantic models and layers
* Evaluate and recommend semantic technologies, including graph databases and reasoning engines best suited for handling high-volume, highly interconnected data.
* Partner with AI/ML teams to leverage ontologies and knowledge graphs for advanced use cases including agentic AI context management.
** Qualifications
* *
* Education:

Bachelor’s or Master's degree in Computer Science, Linguistics, Information Science, or a related field with a focus on knowledge representation.
* 6+ years of hands-on experience in the design, development, and maintenance of large-scale, enterprise-level ontologies.
* Expert knowledge of semantic web standards:
Resource Description Framework (RDF), Web Ontology Language (OWL), and SPARQL.
* Significant experience with graph databases (e.g., Neo4j, Stardog, etc.).
* Proven experience with using…