4 of 4 Remote/Hybrid Knowledge Representation Jobs in England

Data Strategy, Metadata Management, Master Data Management, Data Architecture, Data Quality and Data Products.As organisations increasingly seek to unlock business value through semantic interoperability, knowledge-driven architectures and AI-enabled data platforms, we help our clients establish enterprise semantic foundations that enable trusted, reusable and interoperable data assets.This role … focused on delivering the Semantic Layer Programmes, supporting the development of supporting the design and adoption of enterprise ontologies, semantic standards, controlled vocabularies and knowledge graph capabilities across complex client environments.PLEASE NOTE:Security Clearance: To be successfully appointed to this role, must be eligible to obtain Security Check ...

LEAD DATA SCIENTIST Security Knowledge Graphs & Cyber AI Lead Experience 10+ years overall; 5+ years in AI/ML or graph analytics Location Flexible/Hybrid Employment Type Full-time Role Purpose Lead the design, engineering, and operationalization of enterprise Security Knowledge Graphs that connect security telemetry, assets … modeling, and technical leadership to enable attack-path analysis, threat investigation, exposure prioritization, GraphRAG , and AI-assisted security operations. Key Responsibilities Design the Security Knowledge Graph architecture, ontology, taxonomy, entity model, relationship model, provenance model, and lifecycle standards. Build production-grade graph ingestion and transformation pipelines for SIEM ...

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent Turn complex data into connected knowledge that drives smarter decisions. The Role Financial services firms face significant challenges – and opportunities – in how they manage and extract value from increasingly complex data. Their ability to compete, comply and transform depends … connecting information across data silos and turning it into knowledge that people and machines can meaningfully understand. Graph and Semantics Engineering are emerging enterprise data technologies that use ontologies, advanced analytics and AI to represent knowledge in expressive and innovative ways. Next-generation AI systems powered by knowledge ...

LLMs models for domain-specific tasks. Build evaluation infrastructure and benchmarking pipelines to compare model performance across multiple datasets and tasks. Apply reinforcement learning, knowledge representation, and automated decision-making to solve complex problems end-to-end. Data Infrastructure Collaborate with Data Scientist to build and own data ...