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# Knowledge Graph & GenAI Data Scientist

- **Company:** Global Ltd
- **Location:** UK
- **Experience:** Expert
- **Salary:** £182,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Extract Transform Load (ETL), Query Languages, Graph Database, Design of User Interfaces, Neo4j, SPARQL, Systems Integration, Google Cloud, Data Ingestion, Large Language Models, Containerization
- **Published:** August 14, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/x/43377588/

## About the Role

5+ years in engineering, data, or AI rolesDeep experience with at least one graph technology: Neo4j, TigerGraph, ArangoDB, OrientDB, or StardogProficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.)Strong background in pipelines, ETL, and entity resolutionExposure to integrating KG + LLM or RAG architecturesExperience with graph algorithms, embeddings, or GNNsCloud & production engineering literacy (AWS/Azure/GCP, containerization, CI/CD)Excellent communication skills - able to explain complex graph/AI concepts to non-technical audiences

Nice-to-Have / Bonus Assets

Experience with GraphRAG or KG-backed LLM retrievalSemantic web / ontology skills (RDF/OWL/SHACL)Prior consulting or client delivery backgroundGraph visualization / UI experience (Linkurious, Bloom, Ogma)Graph DB certifications (Neo4j, Stardog, etc.)High visibility & critical client impactExposure to cutting-edge hybrid AI / KG architecturesAutonomy, ownership, and fast learningCompetitive compensation + meaningful equity or bonus schemeFlexible / hybrid work arrangement

## Description

Lead KG schema & ontology design across domains (assets, risk, supply chain, compliance)Build ingestion pipelines (ETL / streaming / CDC) and entity resolution for graph populationAuthor complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack)Integrate knowledge graph retrieval & reasoning into LLM / RAG / GraphRAG systemsDevelop and evaluate graph ML / embedding models (link prediction, anomaly detection)Optimize graph performance, scaling, and query efficiencyLiaise with client stakeholders: translate business problems into graph solutionsMentor junior engineers, contribute to propositions, and support POCs


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