1 to 25 of 114 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 ...

usability. Valuable additional experience Production AI/ML or generative-AI data architecture, including RAG, embeddings, vector search or model-data pipelines. Knowledge graphs, ontologies, RDF, linked data or advanced semantic technologies. Databricks or cloud architecture/data-engineering certification. Tools such as dbt, Kafka, Airflow, Terraform, Power BI, Tableau ...

/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 ...

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 Azure, alongside modern platforms such as Snowflake. Experience designing architectures for unstructured data, knowledge graphs, semantic models, metadata frameworks, taxonomies, ontologies, or enterprise search solutions using technologies such as RDF, OWL, SPARQL, or similar. Understanding of AI technologies, including large language models, vector databases, semantic search and Retrieval ...

lineage and constraintsEnsure requirements include data quality, metadata and governance needs (e.g. definitions, business rules, reference data, retention)Contribute to and consume business glossaries, ontologies and data catalogues to ensure consistent terminology and understandingHelp ensure AI use cases comply with data privacy, security and regulatory requirements (e.g. GDPR, sector specific ...

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 ...

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 ...

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 ...

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 ...

schemas, and project lifecycles (Agile preferred)Bonus Points ForHands-on experience with data modelling tools such as Erwin, Sparx, Visual ParadigmExperience working with ontologies and knowledge of RDF/OWL/TTLExposure to Python or SQL scripting in support of data model designKnowledge of data governance and enterprise metadata integration ...

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 ...

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 ...

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 ...

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 ...

business aligned. Partner with data and analytics engineering teams to design AI-ready data architectures, including data structures, metric layers, semantic models and ontologies, while developing and evaluating proof of concepts to validate emerging technologies, architectural patterns and AI capabilities. Define and champion enterprise-wide standards, governance and best practices ...

anything gets built. Map and prepare the data estate: work alongside the customer's quants and data owners to understand the estate and its ontology, then join unstructured sources (research, filings, news, broker commentary, chat) to structured market and trade data. Point-in-time correctness, corporate actions, symbology and survivorship ...

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 ...

evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks and AI techniques. Integrate scientific metadata, ontologies, taxonomies, and knowledge assets into scalable AI workflows. Establish robust evaluation, experimentation, and monitoring frameworks to ensure quality, trust, performance, and reliability. Write production-ready Python ...

Python development and AI prototyping skills. And any experience of this would be really useful Knowledge of semantic layers and metrics modelling. Experience of ontologies, knowledge representation, taxonomy development and metadata design. Exposure to knowledge graphs, graph-based reasoning concepts, NL2SQL, Text-to-SQL, conversational analytics, dialogue with data approaches ...

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 ...