8 of 8 Permanent Ontologies Jobs in the UK excluding London

streaming responses, async inference jobs, and robust error/retry semantics. Palantir Foundry Integration Work with Palantir Foundry to build and maintain data pipelines, ontologies, and integrations that connect backend services to Foundry-based analytics and workflows. Leverage Foundry's APIs and tooling to support data modelling, transformation, and secure ...

organisation. Key responsibilities include: Driving enterprise data modelling and governance through the Data Architecture Framework (DAF) Developing conceptual and logical models (UML), taxonomies, ontologies and data glossaries Mapping data flows and establishing lineage across the enterprise ecosystem Supporting and evolving the Microsoft D365 and downstream medallion data architecture Administering ...

with stakeholders across engineering, operations, and leadership. What You Will Be Doing: Design and deliver enterprise-scale solutions on Palantir Foundry Build data pipelines, ontologies, and operational applications Develop data products and decision intelligence tools used day-to-day Translate complex operational problems into scalable technical solutions Contribute to platform … modern data architectures & distributed systems Ability to work in fast-paced, ambiguous environments Excellent stakeholder engagement and communication skills Experience building: Data pipelines & transforms Ontologies and data models Operational workflows/application Desirable Experience: Experience with Palantir AIP or AI-enabled workflows Exposure to LLMs or agentic AI systems Cloud ...

/Health IT, disease registries, and claims databases Expertise in clinical data standards, medical terminologies and controlled vocabularies used in healthcare data and ontologies Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data Expertise in methods development and application using languages - strong SQL skills ...

robust, secure, and high-performing data The VP of Data Engineering will establishenabling the development of AI-ready data ecosystems, including knowledge graphs, ontologies, and semantically enriched datasets that support advanced analytics, machine learning, and AI-native applications. best-in-class engineering practices, enabling domain-oriented data ownership while ensuring … shared standards, governance, and platform capabilities. A critical aspect of the role is **Role Responsibilities** Champion the creation and integration of knowledge graphs and ontologies to enhance data discoverability, interoperability, and contextual understanding **Key Skills and Experience** Proven experience leading large-scale data engineering organizations in complex, federated or matrixed ...

Lead Knowledge Graph Engineer/Ontology Engineer - Contract Duration: 6 months (extendable) Rate: £600 per day IR35: Outside Location: Remote with occasional travel to site The Role A leading Regulatory Tech company is seeking a Contract Lead Knowledge Graph Engineer/Ontology Engineer, to support a range of initiatives throughout … this role, you will have the opportunity to: Harness W3C semantic standards and tooling - RDF/RDFS, SPARQL, OWL, SHACL-together with graph databases, ontology-design tools, and visualization platforms such as Linkurious. Apply modern NLP/NLU techniques, from topic modelling to cutting edge entity and relation extraction, plus ...

grounded agents, and structured decision-support systems. Work with knowledge-based AI architectures, including retrieval-augmented generation, knowledge graphs, symbolic rules, structured domain models, ontologies, and hybrid reasoning systems. Develop and apply mechanisms for controlling inference, including planning constraints, reasoning policies, guardrails, validation layers, tool-use control, and human … academic research, or ideally both. Hands-on exposure to knowledge-based agentic systems, such as agents grounded in knowledge graphs, structured documents, domain rules, ontologies, databases, or retrieval systems. Experience with methods for controlling reasoning or inference, such as guardrails, constrained planning, validation layers, policy-based tool use, symbolic checks ...

strategy across data harmonisation, pipeline validation, knowledge graph, and FAIR data product requirements. Requirements Translation: Translate ambiguous scientific requirements into clear canonical data models. Ontology Management: Make ontology reuse, extension, and mapping decisions (with documented rationale), and define persistent identifiers and consistent provenance fields. Risk Mitigation: Identify modelling risks early … including metadata gaps, ontology conflicts, source data quality issues, lineage gaps, and downstream compatibility risks. Design & Architecture: Design modular, reusable, and future-proof models aligned to FAIR principles (findability, accessibility, interoperability, reusability) and enterprise standards. Technical Implementation: Apply practical experience with LinkML (or equivalent), including classes, slots, ranges, identifiers, constraints ...