use, knowledge organization, data modeling, and machine learning Understand and adhere to W3C standards related to ontologies, in particular RDF, RDFS, OWL, SKOS, and SHACL Develop standards, guidelines, and direction for ontology, data modeling, semantics and Data Standardization in general at Capital One Role-Based Competencies Able to develop and More ❯
use, knowledge organization, data modeling, and machine learning Understand and adhere to W3C standards related to ontologies, in particular RDF, RDFS, OWL, SKOS, and SHACL Develop standards, guidelines, and direction for ontology, data modeling, semantics and Data Standardization in general at Capital One Role-Based Competencies Able to develop and More ❯
use, knowledge organization, data modeling, and machine learning Understand and adhere to W3C standards related to ontologies, in particular RDF, RDFS, OWL, SKOS, and SHACL Champion standards, guidelines, and direction for ontology, data modeling, semantics and Data Standardization in general at Capital One Role-Based Competencies Intellectually Curious. You ask More ❯
use, knowledge organization, data modeling, and machine learning Understand and adhere to W3C standards related to ontologies, in particular RDF, RDFS, OWL, SKOS, and SHACL Champion standards, guidelines, and direction for ontology, data modeling, semantics and Data Standardization in general at Capital One Role-Based Competencies Intellectually Curious. You ask More ❯
use, knowledge organization, data modeling, and machine learning Understand and adhere to W3C standards related to ontologies, in particular RDF, RDFS, OWL, SKOS, and SHACL Champion standards, guidelines, and direction for ontology, data modeling, semantics and Data Standardization in general at Capital One Role-Based Competencies Intellectually Curious. You ask More ❯
for text generation and accessibility tools. Comprehensive knowledge of Semantic Web technologies (RDF/s, OWL), query languages (SPARQL) and validation/reasoning standards (SHACL, SPIN). Comprehensive knowledge of RAG and GraphRag systems and architecture. Experience building ontologies in the e-commerce and semantic search spaces. Knowledge Graph and More ❯
and data models, ensuring their effectiveness and usability in real-world applications for both generic and domain-specific applications (e.g., oncology), formalized using OWL, SHACL, and UML. (Meta)data schema development : Create and refine (meta)data schemas to align with international standards, ensuring consistency and interoperability across projects. Interoperability: Develop More ❯
project, which is an internal process automation system, partially related to IoT. Requirements: .Net 8 EF Core 8 Mediatr, FluentValidation Web API Graphs - RDF, SHACL, SPARQL queries unit tests (nUnit/xUnit) modular monolith for the core project (mediatr commands/events) and http/queue connection with side-applications More ❯
