1 to 25 of 92 Taxonomies Jobs in England

data modeling efforts for Product entities including Item, Variant, Product Hierarchy, Pricing, Attributes, and Relationships. Collaborate with business stakeholders to define data standards, taxonomies, and hierarchies for product data. Integrate PIM systems with MDM platforms and downstream applications (e.g., ERP, CRM, data platform). Define and implement data quality rules ...

data modeling efforts for Product entities including Item, Variant, Product Hierarchy, Pricing, Attributes, and Relationships. Collaborate with business stakeholders to define data standards, taxonomies, and hierarchies for product data. Integrate PIM systems with MDM platforms and downstream applications (e.g., ERP, CRM, data platform). Define and implement data quality rules ...

workflow for the new Motorsport UK website, Knowledge Hub and associated digital infrastructure. Coordinate scoping, UX/design reviews, content requirements, information architecture and taxonomy workshops, roadmap planning and delivery cycles. Own internal task management, brief consolidation, approvals, QA, user acceptance testing (UAT) and launch readiness. Maintain clear documentation, roadmaps ...

quality issues and improvement opportunities Play a key role in the organisation’s SAP/S4 transformation programme Audit, cleanse and enhance data structures, taxonomies and mapping Drive cross-functional collaboration and champion data governance across all core systems Ensure compliance for Intrastat, commodity codes, Waste Packaging, WEEE ...

prompt templates, automated workflows with AI tools, or helped customers implement AI features in production Organised data for AI - you've structured spreadsheets, built taxonomies, or created knowledge bases that AI systems can actually parse and use effectively Tested systematically - you've compared outputs across different prompts, tracked what works ...

prompt templates, automated workflows with AI tools, or helped customers implement AI features in production Organised data for AI - you've structured spreadsheets, built taxonomies, or created knowledge bases that AI systems can actually parse and use effectively Tested systematically - you've compared outputs across different prompts, tracked what works ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...

stakeholders on how to best query the new data. Required Skills Technical & Domain Expertise: ● Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, 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 ...