1 to 25 of 127 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 ...

state assessments, architecture diagrams, data inventories and maturity assessments. Define the high-level target data architecture, technology stack and governance framework. Contribute to data ontology design for AI/analytics use cases and the overall data strategy roadmap. Present findings and recommendations to senior client stakeholders and support stakeholder sign ...

/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 ...

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 ...

Doing Designing and developing scalable solutions within Palantir Foundry Building data pipelines, data models and data integration solutions Developing and maintaining Foundry Ontologies Creating high-quality, governed data assets for operational, analytical and AI use cases Building user-facing applications using low-code and pro-code capabilities Working directly with ...

Doing Designing and developing scalable solutions within Palantir Foundry Building data pipelines, data models and data integration solutions Developing and maintaining Foundry Ontologies Creating high-quality, governed data assets for operational, analytical and AI use cases Building user-facing applications using low-code and pro-code capabilities Working directly with ...

generative AI solutions. Experience with agentic development patterns, including tool use, workflow orchestration, and evaluation of agent behavior. Experience with semantic layers and ontology design, including defining consistent business concepts, relationships, and metadata for analytics and AI use cases. Relevant AWS AI certifications, such as AWS Certified AI Practitioner ...

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 ...

autonomous and semi‐autonomous agent workflows that retrieve, reason over, and act on enterprise data (with guidance on architecture and safety). Semantic Layers & Ontologies – Contribute to semantic models (metrics, definitions, and metadata) that make it easier for business users to query data consistently. LLM‐Powered Analytics – Prototype LLM‐enabled ...

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 ...

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 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 ...

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 ...

aligning technical outcomes with business value Nice to have Experience applying AI in drug discovery, safety monitoring or clinical development contexts Understanding of biomedical ontologies or knowledge graph applications Knowledge of regulatory frameworks (FDA, EMA) and experience with data privacy considerations Background in computational biology, biostatistics or related scientific discipline ...

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 ...

analytics platform. E.g from functional genomics and perturbation screens, molecular profiling and expression atlases, genomic and functional annotations, and curated interaction, pathway and ontology resources. Implement production quality code for processing, transforming and quality control of new data types for integration into our larger data model Contribute to and implement ...

Product Management, including product vision, roadmaps, backlog prioritisation, user discovery, iterative delivery and benefits realisation. Demonstrable subject-matter knowledge of enterprise data modelling, ontologies, semantic data, metadata, data governance or related data architecture capabilities. Proven ability to translate ambiguous business and technical needs into clear problems, product requirements, priorities ...

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 graphs can help organisations manage complexity ...

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 ...

Data – Partner with dashboard product owners to shape their dashboards into an AI-ready form the agent can query cleanly and reliably. Semantic Layers & Ontologies – Contribute to semantic models (metrics, definitions, and metadata) so a given metric means the same thing everywhere it's asked about, however the question ...

commercial risk. The Sayari Commercial World Model resolves 11.7B+ primary-source records from 250+ jurisdictions forming the ground truth of global commerce. A Judgment Ontology, encoding over a decade of investigative tradecraft, and Superconductor, an agentic orchestration platform, deliver AI that reasons like an expert analyst, shows its work ...