1 to 25 of 241 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 ...

/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 ...

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 ...

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 ...

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 ...

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 ...

Palantir Foundry experience. Key Responsibilities Design, develop, and maintain end-to-end data pipelines using Palantir Foundry , including Pipeline Builder, Code Repositories, Data Lineage, Ontology, Workshop, Quiver, and related Foundry capabilities. Implement batch, incremental, and streaming ETL/ELT workflows using reusable, scalable, and production-ready components. Build and maintain … business and analytical requirements. Work across federated data environments , integrating diverse data sources and addressing complex data integration challenges. Design, extend, and maintain Foundry Ontologies , including object types, link types, property types, and semantic relationships. Develop semantic data layers that support analytics, operational workflows, automation, and machine learning use cases ...

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 ...

maintain knowledge graph structures that reflect canonical domain models. Develop and manage graph database schemas, queries, and data ingestion pipelines. Ensure semantic consistency between ontology definitions and downstream data products. AI & Vector Infrastructure Design and implement embedding pipelines that represent Comply’s financial and regulatory data in vector space. Build ...

maintain knowledge graph structures that reflect canonical domain models Develop and manage graph database schemas, queries, and data ingestion pipelines Ensure semantic consistency between ontology definitions and downstream data product AI & Vector Infrastructure Design and implement embedding pipelines that represent Comply’s financial and regulatory data in vector space Build ...

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 ...

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 ...

maintain knowledge graph structures that reflect canonical domain models • Develop and manage graph database schemas, queries, and data ingestion pipelinesEnsure semantic consistency between ontology definitions and downstream data product AI & Vector InfrastructureDesign and implement embedding pipelines that represent Comply's financial and regulatory data invector spaceBuild and operate vector database ...

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 ...

such as research, building domain knowledge, or prototyping. Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will ...

such as research, building domain knowledge, or prototyping. Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will ...

such as research, building domain knowledge, or prototyping. Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will ...

such as research, building domain knowledge, or prototyping. Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will ...

such as research, building domain knowledge, or prototyping. Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will ...

such as research, building domain knowledge, or prototyping. Nice to have: exposure to the building blocks of AI-ready data, such as semantic layers, ontologies, or text-to-SQL, plus any experience applying AI operationally within data platforms or pipelines. This won't be your main focus, but it will ...