51 to 72 of 72 SPARQL Jobs

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

Properties) ● Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities. ● Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus. ● AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground ...

implement, and maintain ETL pipelines to prepare data for graph-based structures. Develop and optimize graph database solutions using querying languages such as Cypher, SPARQL, or GQL. Neo4J DB experience is preferred. Build and maintain ontologies and knowledge graphs, ensuring efficient and scalable data modeling. Integrate vector databases and implement … working with Graph DB. Engineering experience within AWS systems is highly preferred Programming: Proficiency in Python and PySpark programming. Querying: Advanced knowledge of Cypher, SPARQL, or GQL querying languages. ETL Processes: Expertise in designing and optimizing ETL processes for graph structures. Data Modeling: Strong skills in creating ontologies and knowledge ...