1 to 25 of 39 Ontologies Jobs in the UK excluding London

AWS, Azure, GCP). Strong communication and stakeholder engagement skills - translating complex technical concepts into business outcomes. Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A "can-do" mindset and hunger for continuous learning. Why More ❯

AWS, Azure, GCP). Strong communication and stakeholder engagement skills — translating complex technical concepts into business outcomes. 💡 Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A “can-do” mindset and hunger for continuous learning. 🌍 Why More ❯

AWS, Azure, GCP). Strong communication and stakeholder engagement skills translating complex technical concepts into business outcomes. Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A can-do mindset and hunger for continuous learning. Why More ❯

AWS, Azure, GCP). Strong communication and stakeholder engagement skills translating complex technical concepts into business outcomes. Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A can-do mindset and hunger for continuous learning. Why More ❯

experience designing and managing data architectures using Snowflake and AWS environments at scale. Excellent leadership, collaboration and communication skills across large, multi-disciplined organisations. Practical expertise in designing enterprise ontologies and knowledge networks. Strong understanding of dimensional and normalized data modelling techniques. Hands-on expertise in dbt for data transformation and pipeline orchestration. Solid background in data engineering with proficiency More ❯

Principal levels) Extensive knowledge of Drug Discovery, Development/Manufacturing or similar Life Science domain Fluency in Python, Data Modelling, Data Integration, Analysis and Visualisation (tabular & JSON, SQL, NoSQL, Ontologies, Streamlit, Plotly, Holoviews) A track record of architecting productionised scientific solutions , integrated with AI/ML and APIs for Biopharma end users Strong communication skills to engage across leadership, scientific More ❯

Principal levels) Extensive knowledge of Drug Discovery, Development/Manufacturing or similar Life Science domain Fluency in Python, Data Modelling, Data Integration, Analysis and Visualisation (tabular & JSON, SQL, NoSQL, Ontologies, Streamlit, Plotly, Holoviews) A track record of architecting productionised scientific solutions , integrated with AI/ML and APIs for Biopharma end users Strong communication skills to engage across leadership, scientific More ❯

Principal levels) Extensive knowledge of Drug Discovery, Development/Manufacturing or similar Life Science domain Fluency in Python, Data Modelling, Data Integration, Analysis and Visualisation (tabular & JSON, SQL, NoSQL, Ontologies, Streamlit, Plotly, Holoviews) A track record of architecting productionised scientific solutions , integrated with AI/ML and APIs for Biopharma end users Strong communication skills to engage across leadership, scientific More ❯

Degree in Life Sciences, Data Science, Computer Science, or a related field. 2+ years' experience in data curation, data management or data governance. Working knowledge of data standards, models, ontologies and taxonomies. Experience with tools such as Semaphore, Collibra, Protégé, or similar. Strong communication and stakeholder-management skills. More ❯

for automated enrichment and agentic features. Develop entity-matching algorithms (potentially using ML) to link disparate data points and resolve entities. Work with domain experts to formalise a comprehensive ontology of the chemical and energy supply chain. Build agent-based systems that perform complex automated tasks, updating the digital twin based on real-time data. Establish the foundations for MLOps More ❯

for automated enrichment and agentic features. Develop entity-matching algorithms (potentially using ML) to link disparate data points and resolve entities. Work with domain experts to formalise a comprehensive ontology of the chemical and energy supply chain. Build agent-based systems that perform complex automated tasks, updating the digital twin based on real-time data. Establish the foundations for MLOps More ❯

for automated enrichment and agentic features. Develop entity-matching algorithms (potentially using ML) to link disparate data points and resolve entities. Work with domain experts to formalise a comprehensive ontology of the chemical and energy supply chain. Build agent-based systems that perform complex automated tasks, updating the digital twin based on real-time data. Establish the foundations for MLOps More ❯

for automated enrichment and agentic features. Develop entity-matching algorithms (potentially using ML) to link disparate data points and resolve entities. Work with domain experts to formalise a comprehensive ontology of the chemical and energy supply chain. Build agent-based systems that perform complex automated tasks, updating the digital twin based on real-time data. Establish the foundations for MLOps More ❯

data integrity. Work with Python to build scalable data solutions. Introduce and adopt new technologies such as Kafka, Docker, Airflow, and AWS . Define and enforce data hygiene practices (ontology, storage, artifacts, version control). Reduce engineering load per person through automation and efficient design. Collaborate closely with a small, ambitious team to deliver end-to-end data solutions. Support More ❯

data integrity. Work with Python to build scalable data solutions. Introduce and adopt new technologies such as Kafka, Docker, Airflow, and AWS . Define and enforce data hygiene practices (ontology, storage, artifacts, version control). Reduce engineering load per person through automation and efficient design. Collaborate closely with a small, ambitious team to deliver end-to-end data solutions. Support More ❯

data integrity. Work with Python to build scalable data solutions. Introduce and adopt new technologies such as Kafka, Docker, Airflow, and AWS . Define and enforce data hygiene practices (ontology, storage, artifacts, version control). Reduce engineering load per person through automation and efficient design. Collaborate closely with a small, ambitious team to deliver end-to-end data solutions. Support More ❯

data integrity. Work with Python to build scalable data solutions. Introduce and adopt new technologies such as Kafka, Docker, Airflow, and AWS . Define and enforce data hygiene practices (ontology, storage, artifacts, version control). Reduce engineering load per person through automation and efficient design. Collaborate closely with a small, ambitious team to deliver end-to-end data solutions. Support More ❯

Deployed Engineer, Palantir FDE Strong programming skills in Python , SQL , and optionally Java/Scala Hands-on experience with Palantir Foundry tools , including: Code Repositories, Pipeline Builder, Code Workbook Ontology Management, Contour, Solution Designer, Data Lineage Data Health, Data Connections, Egress Policies Experience in end-to-end solution development , from planning to scaling Strong understanding of data architecture , including data More ❯

non-technical stakeholders, facilitating discussions with multidisciplinary teams, including military users. Data Integration – build clean, reliable, and compliant pipelines in Foundry using Pipeline Builder and Python. Design and manage ontologies to structure data effectively, leveraging Link Types and Actions for optimal use in Foundry and Workshop. Application Development – create full-stack applications with Foundry tools to deliver intuitive interfaces and More ❯

non-technical stakeholders, facilitating discussions with multidisciplinary teams, including military users. Data Integration – build clean, reliable, and compliant pipelines in Foundry using Pipeline Builder and Python. Design and manage ontologies to structure data effectively, leveraging Link Types and Actions for optimal use in Foundry and Workshop. Application Development – create full-stack applications with Foundry tools to deliver intuitive interfaces and More ❯

of contemporary data management principles. Experience of working within, and influencing, international collaborations, including those within the Photon and Neutron community. Knowledge of the use of FAIR vocabularies and ontologies, Persistent Identifiers and metadata schemas (e.g. DataCite and domain-specific vocabularies). Ability to present complex concepts to both specialist and non-specialist audiences. Skills in managing multiple projects and More ❯

Location: London UK (hybrid) Type: Permanent or contract-to-perm Own the enterprise knowledge graph and GraphRAG platform powering search, Q&A, and agentic apps. ROLE PROFILE: Model the ontology/schema and build governed ingestion (NER/NEL, dedupe/merge, provenance). Deliver hybrid retrieval (graph traversal + embeddings + rerank ) with measured uplift. Expose secure APIs/ More ❯

Location: London | UK (hybrid) | Type: Permanent or contract-to-perm Own the enterprise knowledge graph and GraphRAG platform powering search, Q&A, and agentic apps. ROLE PROFILE: Model the ontology/schema and build governed ingestion (NER/NEL, dedupe/merge, provenance). Deliver hybrid retrieval (graph traversal + embeddings [+ rerank]) with measured uplift. Expose secure APIs/ More ❯

Location: London | UK (hybrid) | Type: Permanent or contract-to-perm Own the enterprise knowledge graph and GraphRAG platform powering search, Q&A, and agentic apps. ROLE PROFILE: Model the ontology/schema and build governed ingestion (NER/NEL, dedupe/merge, provenance). Deliver hybrid retrieval (graph traversal + embeddings [+ rerank]) with measured uplift. Expose secure APIs/ More ❯

Location: London | UK (hybrid) | Type: Permanent or contract-to-perm Own the enterprise knowledge graph and GraphRAG platform powering search, Q&A, and agentic apps. ROLE PROFILE: Model the ontology/schema and build governed ingestion (NER/NEL, dedupe/merge, provenance). Deliver hybrid retrieval (graph traversal + embeddings [+ rerank]) with measured uplift. Expose secure APIs/ More ❯