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.