51 to 75 of 90 Ontologies Jobs in England

Data-as-a-Service as a real product — a secure, multi-tenant, immutable release architecture, with data made discoverable at scale through catalogue and ontology-driven search, in partnership with the data team.Powering agentic AI from the data platform — scaling the data foundations behind MystraAI and owning secure, tenant-scoped ...

data assets.This role will be primarily 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 … Standards, Controlled Vocabularies, Data Contracts, Semantic Data Products and Knowledge Graph implementations.This is a senior client-facing leadership role requiring deep technical expertise in ontology engineering, semantic technologies and knowledge representation, combined with the ability to engage senior stakeholders and facilitate consensus across business and technology teams.The successful candidate will ...

assets. This role will be primarily 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 … Controlled Vocabularies, Data Contracts, Semantic Data Products and Knowledge Graph implementations. This is a senior client-facing leadership role requiring deep technical expertise in ontology engineering, semantic technologies and knowledge representation, combined with the ability to engage senior stakeholders and facilitate consensus across business and technology teams. The successful candidate ...

enterprise data architectures, cloud data platforms, and data integration strategies. Information Architecture: Establishes the enterprise-wide business glossary, conceptual data blueprints, and taxonomy/ontology frameworks to ensure a unified understanding of data across the business. Data Modeling: Oversees the creation and maintenance of enterprise conceptual, logical and physical data … secure data pipelines. Information Architect Deep expertise in metadata management, master data management (MDM), and reference data management. Proven ability to construct enterprise taxonomies, ontologies, data lineages, and business glossaries. Strong understanding of semantic web technologies (RDF, OWL, Knowledge Graphs). Data Modeler Expert proficiency in industry-standard data modeling ...

part of their implementation ofSuccessFactors.You will also have opportunities to support clients in embedding skills‐based hiring, leveraging SAP Talent Intelligence Hub (TIH), Skills Ontologies and skills metadata to optimise job design, sourcing, screening and internal mobility workflows.This role combines hands‐on configuration, solution design, client advisory and the opportunity ...

part of their implementation ofSuccessFactors.You will also have opportunities to support clients in embedding skills‐based hiring, leveraging SAP Talent Intelligence Hub (TIH), Skills Ontologies and skills metadata to optimise job design, sourcing, screening and internal mobility workflows.This role combines hands‐on configuration, solution design, client advisory and the opportunity ...

time-series and multimodal data, simulation and world models, trustworthy decision-support agents and staged autonomy, and AI-native approaches to industrial data foundations, ontology learning, and evaluation.This is a hands-on role for someone who thrives in uncertain problem spaces, works with high autonomy, and finds practical ways ...

time-series and multimodal data, simulation and world models, trustworthy decision-support agents and staged autonomy, and AI-native approaches to industrial data foundations, ontology learning, and evaluation.This is a hands-on role for someone who thrives in uncertain problem spaces, works with high autonomy, and finds practical ways ...

prem vs cloud). Provide technical input into the development of Digital strategies and Intelligent Building policies for clients, including best practice data structures & ontologies and design parameters for digital enablement.Provide expert advice on cyber security for operational technologies, including vulnerability assessments and compliance with standards such as IEC 62443.Maintain ...

prem vs cloud). Provide technical input into the development of Digital strategies and Intelligent Building policies for clients, including best practice data structures & ontologies and design parameters for digital enablement.Provide expert advice on cyber security for operational technologies, including vulnerability assessments and compliance with standards such as IEC 62443.Maintain ...

tune – Codify the firm’s unwritten methods and judgements into the coworkers and playbooks that run at machine speed. Anchor them through the ontology and semantic layers in Celeste so the agents reason the way its own people do. Earn adoption – Lead the actions that earns Celeste’s adoption, from ...

high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms Own the architecture of the enterprise context layer — knowledge graphs, ontologies, vector search, and semantic retrieval — grounding the solution in client knowledge Set the design direction for context assembly and memory that manages prompts, context windows ...

tune – Codify the firm's unwritten methods and judgements into the coworkers and playbooks that run at machine speed. Anchor them through the ontology and semantic layers in Celeste so the agents reason the way its own people do. Earn adoption – Lead the actions that earns Celeste's adoption, from ...

LLMs, retrieval‐augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding‐model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM‐as‐judge, groundedness and faithfulness metrics, tracing), and model risk controls. Experience building secure, scalable … closely with subject matter experts to refine AI tools iteratively and turn specialist feedback into practical product improvements. Strong grasp of structured data, taxonomies, ontology‐style data models and mappings across complex standards or schemas. Experience with user testing, controlled pilots, adoption planning, training and feedback loops for specialist user ...

Lead to manage the successful delivery of a large-scale enterprise Knowledge Graph programme. The role will lead cross-functional teams across data architecture, ontology design, data engineering, graph engineering, business analysis, and platform delivery to ensure the successful implementation of a strategic knowledge graph capability. The successful candidate will … delivery of the Knowledge Graph programme, ensuring alignment with business outcomes, timelines, budgets, and quality objectives. Lead multidisciplinary teams spanning architecture, ontology design, data engineering, graph engineering, and business stakeholders. Establish and drive delivery plans, governance structures, risk management processes, and reporting mechanisms. Manage dependencies across multiple workstreams, technology teams ...

privacy, and risk management.Ensure the team makes evidence-based decisions and communicates results clearly to stakeholders.Stakeholder collaborationWork closely with product managers, engineers, content specialists, ontology experts, biomedical informaticians, and commercial stakeholders.Translate customer and business needs into clear data science opportunities, project plans, and measurable outcomes.Communicate technical findings, trade-offs, risks … platforms such as Databricks, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, MLflow, or similar.Preferred qualificationsExperience in life sciences, pharmaceuticals, chemistry, biomedical research, clinical data.Familiarity with ontologies, taxonomies, controlled vocabularies, and metadata standards.Experience with NLP, entity extraction, entity linking, semantic enrichment, search, ranking, recommendation, or knowledge graph methods.Exposure to production ML systems ...

NIST AI RMF and enterprise governance standards Data, Semantic & Knowledge Architecture Support development of enterprise semantic and knowledge capabilities Define architecture approaches for: enterprise ontologies semantic models metadata-driven platforms knowledge graph integration unstructured data processing Ensure trusted and governed data foundations underpin AI-enabled capabilities Collaborate with data architecture … operational teams Experience influencing senior stakeholders within matrixed organisations Technical skills AI orchestration and agentic workflow architectures RAG and GraphRAG architectures Knowledge graphs, ontologies and semantic technologies Vector databases and semantic retrieval patterns Microsoft Fabric, Azure AI and modern cloud platforms API and integration architecture Enterprise security and identity models ...

technical expectations. Customer Advisory: Provide remote and on-site technical advisory services to customers, offering guidance on data attributes, integration strategies, and system optimization. Ontology & Model Development: Advise on the evolution of Janes data models and ontologies to ensure compatibility and seamless integration with customer ecosystems. Gap Analysis: Identify ...

fund data for one of the world's largest asset managers. You will encode business rules, regulatory constraints, and identifier relationships as machine-readable ontologies — directly eliminating manual fund data processes and enabling automated validation across thousands of funds in 6 global markets. Defined POC scope, executive sponsorship, and weekly … technical guidance from two of the most recognized knowledge graph practitioners in financial services.What You'll Deliver (POC Scope)An investment fund ontology (OWL 2/RDF/Linked Data) modeling the product hierarchy: Fund > ShareClass > Listing > Security, with 73+ identifier types (ISIN, SEDOL, CUSIP, LEI, Bloomberg, and more) governed ...

data foundations that enable Patient Solutions to scale trusted, reusable and AI-ready data across Research and Early Development.You will define and govern metadata, ontologies, identifiers and data standards that improve data quality, interoperability and discoverability. Working across scientific, digital and enterprise teams, you will help shape how data … Governance and AI teams to ensure data foundations are aligned with enterprise standards while meeting evolving scientific needs.What you’ll doEstablish and govern enterprise ontologies, business vocabularies and global identifiers to ensure consistent representation and traceability of data across Patient Solutions.Design and implement scalable metadata management capabilities that improve data ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph‐based ML models (functional + technical) Experience with end‐to‐end data pipeline ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with end‐to‐end data pipeline ...

engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with … degree or equivalent, plus at least 3 of the following:Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)Experience in schema design, ontology management, and KG curationExpertise in designing and developing KG solutions and graph-based ML models (functional + technical)Experience with end-to-end data pipeline implementation ...

public sector) Embed client strategy and technical teams Stretching the frontier: hybrid KG + AI, graph + reasoning + M 🛠 Responsibilities Lead KG schema & ontology design across domains (assets, risk, supply chain, compliance) Build ingestion pipelines (ETL/streaming/CDC) and entity resolution for graph population Author complex queries …/AI concepts to non-technical audiences ✅ Nice-to-Have/Bonus Assets Experience with GraphRAG or KG-backed LLM retrieval Semantic web/ontology skills (RDF/OWL/SHACL) Prior consulting or client delivery background Graph visualization/UI experience (Linkurious, Bloom, Ogma) Graph DB certifications (Neo4j, Stardog ...

integrate emerging technologies into the team’s roadmap. Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems. Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems. Incorporate structured data — including datasets, chemical entities, genes, drugs … Computer Science, Data Science, Machine Learning, or a related field Experience working with large‐scale datasets (scientific, biomedical, or enterprise data) Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef) Exposure to production ML systems and MLOps practices Familiarity with data visualization and analytical tooling (e.g., Tableau ...