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Data Scientist

Shreeya MirashiUnited KingdomMIDPosted 13d ago
Knowledge GraphsGraph Data ScienceData EngineeringGenAIGraphRAGontology designsemantic modellingRDFproperty graphsgraph schemasdata provenanceNeo4jCypherAmazon NeptuneTigerGraphAzure Cosmos DB Gremlingraph algorithmsembeddingslink predictionclusteringanomaly detectionGraph Neural NetworksPythonSQLAPIsdistributed processingtestingGitCI/CDcontainersSparkDatabricksKafkaETLELTbatch/real-time pipelinesLLMMLOps
About the Role We are looking for a Data Scientist to join our team in London, Manchester, or Leeds. This role requires expertise in Knowledge Graphs, Graph Data Science, Data Engineering, and GenAI/GraphRAG to develop scalable, production-ready solutions. Key Responsibilities • Develop scalable, production-ready solutions using Knowledge Graphs, Graph Data Science, and GenAI/GraphRAG • Design and implement ontology design, semantic modelling, RDF, property graphs, graph schemas, and data provenance • Work with graph platforms such as Neo4j, Cypher, Amazon Neptune, TigerGraph, or Azure Cosmos DB Gremlin • Apply graph algorithms, embeddings, link prediction, clustering, anomaly detection, and Graph Neural Networks • Utilize advanced Python and SQL skills, APIs, distributed processing, testing, Git, CI/CD, and containers • Manage data engineering tasks with Spark/Databricks, Kafka, ETL/ELT, and batch/real-time pipelines • Implement GenAI and GraphRAG solutions, including LLM-based extraction, retrieval, prompt design, evaluation, grounding, and guardrails • Cover MLOps aspects such as model deployment, monitoring, versioning, drift detection, observability, and security controls Requirements • Strong experience in ontology design, semantic modelling, RDF, property graphs, graph schemas, and data provenance • Hands-on experience with Neo4j or Cypher, plus knowledge of another graph platform • Expertise in graph algorithms, embeddings, link prediction, clustering, anomaly detection, and Graph Neural Networks • Advanced Python and SQL skills, APIs, distributed processing, testing, Git, CI/CD, and containers • Data engineering experience with Spark/Databricks, Kafka, ETL/ELT, and batch/real-time pipelines • GenAI and GraphRAG experience, including LLM-based extraction, retrieval, prompt design, evaluation, grounding, and guardrails • MLOps experience covering model deployment, monitoring, versioning, drift detection, observability, and security controls Eligibility: UK-based candidates with valid work authorization only. No sponsorship available.

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