1 to 25 of 140 Ontologies Jobs in England

data products aligned to business use cases. Work with federated data environments, handling diverse sources and complex integration requirements. Design, extend, and maintain Foundry ontologies, including object types, link types, property types, and semantic relationships. Build semantic layers that support analytics, operational workflows, and machine learning use cases. Embed strong ...

data products aligned to business use cases. Work with federated data environments, handling diverse sources and complex integration requirements. Design, extend, and maintain Foundry ontologies, including object types, link types, property types, and semantic relationships. Build semantic layers that support analytics, operational workflows, and machine learning use cases. Embed strong ...

provide the contextual foundation required for AI, analytics and knowledge-driven solutions. You will contribute to the development of trusted data products and business ontologies that enable data to be discovered, understood and consumed consistently across Power BI, advanced analytics, Microsoft Copilot, AI agents and future AI-enabled solutions. Working ...

Lake, Azure Data Factory, dbt, Airflow, MLflow, Power BI, Microsoft Purview or comparable tools. Experience with search indexes, vector databases, graph databases, knowledge graphs, ontologies or master-data-management techniques. Experience with MLOps, model monitoring, experimental design, causal inference, forecasting, recommendation systems or optimisation. Experience with legal, financial, client, market ...

/or Google Cloud Platform. ELN or LIMS platforms such as Benchling. Preparing data for analytics, machine learning or AI applications. Semantic modelling, ontologies or knowledge graphs. CI/CD, infrastructure-as-code or other modern software‐engineering practices About Us Tropic is one of the world’s leading agricultural ...

modelling. Strong stakeholder engagement and influencing skills, with the ability to communicate complex concepts to technical and non‐technical audiences Experience developing semantic models, ontologies, taxonomies, business glossaries or knowledge structures. Strong knowledge of metadata, data lineage, data quality, master data management and data governance. Experience defining enterprise architecture principles ...

platform evolution by onboarding new sources, refining deployment templates/workflows, and mentoring engineers on engineering standards. Designing and maintaining a business data ontology with canonical entities, relationships, and shared vocabulary. Stakeholder Engagement & Communication Build and maintain trusted relationships with business stakeholders, data product owners, and reporting teams – acting ...

will help define and drive the capabilities, patterns and practices needed to make enterprise data AI-ready, including semantic layers, knowledge graphs, and ontologies to ensure trusted, governed and scalable use of enterprise data by AI applications and agents. The successful candidate will combine strong knowledge of AI and modern ...

connected R&D data foundations through governance, master data management, interoperability, metadata management, and modern data architectures. Lead the application of semantic technologies, ontologies, RDF-based knowledge graphs, and common data models to create a shared understanding of scientific, research, preclinical, and clinical information across systems.Enable advanced analytics, scientific knowledge ...

deployments end to end for one or more clients, from scoping with their leadership to running production systems Own the architecture for data pipelines, ontologies and AI workflows on Palantir Foundry and AIP Be the technical lead in the room at client senior level: you're the engineer they trust ...

will help define and drive the capabilities, patterns and practices needed to make enterprise data AI-ready, including semantic layers, knowledge graphs, and ontologies to ensure trusted, governed and scalable use of enterprise data by AI applications and agents. The successful candidate will combine strong knowledge of AI and modern ...

business goals. Design the Data-to-AI Interface: Establish how enterprise data is structurally modelled (using star schemas, semantic layers, dimensional modelling, and knowledge ontologies) to ensure autonomous AI agents can search, retrieve, and reason over data reliably without hallucinating. Build AI services: Lead the hands-on design, coding ...

semantic technology. We care more about what you have built and how you approach a problem than a particular tool stack or formal ontology background. You have built a knowledge graph or another connected data application for analytics, content or AI, and can take an idea from domain conversations ...

data discovery platforms Familiarity with semantic web or knowledge graph concepts (e.g., RDF, SKOS, OWL) and experience integrating these into usable data models. Formal ontology design is not required, but ability to collaborate with ontologists is essential Understanding of data governance frameworks or certifications (e.g., DAMA CDMP, DCAM) Exposure ...

Experience analysing or modelling policy, regulatory, or control-related content (e.g., obligations, controls, standards, procedures) Working knowledge of knowledge graphs and graph analytics, including ontology/taxonomy design for entity relationships, citation networks, and controlled vocabularies Familiarity with modern data catalog, lineage, and data modelling tools Exposure to extraction ...

Experience analysing or modelling policy, regulatory, or control-related content (e.g., obligations, controls, standards, procedures) Working knowledge of knowledge graphs and graph analytics, including ontology/taxonomy design for entity relationships, citation networks, and controlled vocabularies Familiarity with modern data catalog, lineage, and data modelling tools Exposure to extraction ...

catalogue initiatives. Able to produce client-ready architecture documents and written review responses without editorial support. Will be a plus: Knowledge of financial-industry ontologies (e.g. FIBO or similar) and a realistic view of their practical limitations. Familiarity with semantic search over metadata based on embeddings. Domain experience in asset ...

Schema & Pipeline Engineering: Develop and maintain end-to-end multi-stream ingestion pipelines for complex clinical trial schemas. Use AI-driven schema inference and ontology alignment tools to auto-draft mapping artifacts, dramatically reducing integration timelines across different life science datasets. High-Throughput Streaming & Backend Services: Build scale, fault-tolerant ...

data and technical teams to turn a framework into usable validation and discovery capabilities. Information catalogues, knowledge management systems, enterprise search and content discoverability. Ontology, semantic modelling or controlled-vocabulary management approaches. Experience with information assurance, data-quality measures and operational stewardship models. Expected contribution: An agreed, version-controlled metadata ...

architecture, Durable workflows, AWS, Databricks, RBAC/ABAC, IAM, observability and infrastructure chargebacks. Data, Knowledge, and Developer Products: Search, Semantic layer foundations, knowledge and ontology layers and products, external developer platforms. What you’ll own: Enterprise Platform: Tenancy, IAM, Compliance and control plane that enterprise customers use to govern their ...

ability to engage effectively with technical teams.* Hands on experience with technical tooling and code development experience* Knowledge of semantic layers, graphs, and ontologies* Experience and curiosity around AI-powered development.* Ability to translate business needs into clear data design, with a focus on enabling decision-making and delivering measurable ...

semantic models, metadata expectations and architecture decision records. Promote consistent information models, data contracts, naming, lineage and contextualization practices, including alignment with enterprise ontology, knowledge-graph and unified namespace approaches where these support approved business outcomes. Establish measures for adoption, reuse, reliability, data quality, service performance, user experience and benefits ...

business analysts and client stakeholders. Typical outputs may include target-state architectures, maturity assessments, platform option appraisals, data product designs, governance models, lineage maps, ontology and semantic models, integration patterns, GenAI data-readiness assessments and implementation roadmaps. We do not expect every candidate to be a specialist in every aspect … management. Design data products, data contracts and information models that make enterprise data reusable across analytics, AI, GenAI and operational workflows. Shape semantic layers, ontologies and knowledge graph patterns where these improve data discoverability, interoperability, explainability or AI consumption. Oversee high-level design of ingestion, integration and transformation patterns, including ...

change how your team builds Nice to Have Snowflake, Databricks and AWS Embeddings, vector search, feature stores or knowledge graphs Taxonomy or ontology design Social, web-scale or licensed third-party data A background in media, information services, SaaS or e-commerce Experience Around 10 or more years in data ...

field environments, including data capture, experimentation, trial execution, automation, sensors, imaging, geospatial data, and data standards. Knowledge of data integrity, discoverability, metadata, taxonomy/ontology, traceability, provenance, auditability, and quality controls across data pipelines. Experience working with data governance, security, architecture, quality, compliance, and regulatory requirements. Strong stakeholder management ...