51 to 64 of 64 Ontologies Jobs

across the Claims value chain.Lead the development and expansion of scalable data pipelines supporting both structured and unstructured claims data.Scale and enhance a Claims ontology and semantic layer that connects structured and unstructured data into a unified business knowledge model, improving discoverability, interoperability, and AI readiness.Collaborate with regional Claims leaders … solutions in production.Hands-on experience with Databricks, Snowflake, Azure Data Platform, Azure AI Search, Azure Data Lake Storage, and modern cloud architectures.Experience developing enterprise ontologies, semantic layers, or knowledge graph solutions.Experience building Retrieval-Augmented Generation (RAG), AI Search, or document intelligence solutions.Experience scaling enterprise data capabilities across multiple regions ...

processes, and day-to-day decision-making rather than limiting it to dashboards and reports.Define the knowledge layer, including core business entities, relationships, taxonomies, ontologies, semantic standards, and entity resolution across key business concepts.Establish governance, trust, evaluation standards, and operating models that support AI-ready knowledge products at scale.Support … platforms, including Spark-based lakehouse environments.Experience preparing proprietary document corpora for AI search, summarization, and reasoning.What makes you stand out Exposure to ontology design, knowledge graphs, semantic modeling, or entity resolution.Working knowledge of enterprise AI governance, model evaluation, responsible AI, or AI risk controls.Hands-on experience building or scaling data ...

foundations with AI, automation, and product innovation across the portfolio.How you will make an impact:Define and own the canonical telco data model and ontology across network topology, service lifecycle, inventory, assurance, and OSS domainsAlign data models with industry standards including TM Forum Open APIs, SID/eTOM, Open Digital … Architecture, YANG/NETCONF, and TOSCADrive adoption of ontology models across product teams as the semantic foundation for data exchange, AI training, and digital twin deploymentDevelop and lead the data fabric product architecture, including federated access, streaming pipelines, virtualization, metadata management, and lineage trackingTranslate data architecture vision into scalable, cloud ...

complex modalities such as genomics, transcriptomics, imaging, clinical and real-world datasets. Partner with the Data Excellence community and IT to align on governance, ontologies, metadata harmonisation, stewardship and shared enterprise data foundations. Establish ways of working and coach other team members, onboarding, mentoring and technically leading data engineers … requirements, including versioning, reproducibility and tensor-based workflows for large-scale AI systems. Experience implementing data governance in practice, including metadata management, lineage, provenance, ontologies, cataloguing and FAIR principles and familiarity with Trusted Research Environments (TREs) and controlled-access research data environments. Strong collaboration and influencing skills across technical ...

completeness. Focus on Material domains and future expansion to other scientific domainsDatabase Development and Maintenance: Contribute to the design and maintenance of our scientific ontology, ensuring efficient data storage, retrieval, domain coverage, and integration with our software platformPipeline Development: Implement ETL pipelines for ingesting, cleaning, and transforming scientific datasets from … analyse scientific data, identify trends, and develop predictive models for domain-relevant properties and behavioursOntology Development and Classification: Develop and maintain a comprehensive scientific ontology and classification system to enable efficient searching and filtering based on substance class, properties, and applicationsIntegration with Software Tools: Collaborate with software engineers to ensure ...

team in London, London, City of (GB-LND), United Kingdom (GB).Job Title: Knowledge Graph ArchitectExperience: 10+ years (5+ years in Knowledge Graphs/Ontology Engineering)Role OverviewWe are looking for a Knowledge Graph Architect to lead the design and governance of enterprise knowledge graphs. This role will define … ontology, data model, and canonical vs. interpretive boundaries, enabling scalable, high-quality graph data for AI-driven use cases, including Graph RAG.The role also requires strong team leadership, including coaching, mentoring, and building internal capabilities.Key ResponsibilitiesArchitecture & DesignDefine node types, relationships, schemas, and property standardsDesign scalable and extensible graph data modelsEstablish ...

integrate emerging technologies into the team’s roadmap.Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems.Domain & Research IntegrationCollaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems.Incorporate structured data — including datasets, chemical entities, genes, drugs, clinical … Computer Science, Data Science, Machine Learning, or a related fieldExperience working with large-scale datasets (scientific, biomedical, or enterprise data)Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef)Exposure to production ML systems and MLOps practicesFamiliarity with data visualization and analytical tooling (e.g., Tableau, Power ...

Data Modeller to help shape how HSBC defines, organises and connects business terms across the Group. You’ll build high-quality glossaries, taxonomies and ontologies that create a shared semantic layer - so our data can be understood consistently and used by AI to answer questions across teams, faster and with … reusable“Join the dots” across teams/domains to help build a shared semantic layer that supports cross-boundary understanding and consistencyContribute to ontology development (the layer between taxonomies) to enable AI to query and reason across multiple teams, products and datasets - turning terminology into a connected, machine-interpretable knowledge ...

science, including literature searching, content analysis, and knowledge synthesisProven ability to translate scientific and business questions into effective search and analysis techniquesFamiliarity with metadata, ontologies, and FAIR data principles for structuring scientific contentWorking knowledge of AI capabilities related to content analysis, such as large language models (LLMs), semantic technologies … cross-functional teamsNice to Have Skills:Practical experience in evaluating, piloting, or advising on AI-driven content toolsKnowledge of data visualization, knowledge graphs, and ontology managementFamiliarity with Python, AI frameworks, and prompt engineering techniques for NLP applicationsExperience with scientific communication tools and knowledge mappingPreferred Education and Experience:Bachelor ...

contribute recommendations for experimentation and adoption. Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts. Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows. Search, Retrieval & RAG Systems Design, develop, and optimize search and retrieval pipelines , including lexical, vector, and hybrid retrieval approaches. … conversational AI applications Experience working on search, ranking, recommendation, or retrieval systems Familiarity with scientific, biomedical, or scholarly datasets Experience with knowledge graphs, ontologies, or semantic enrichment systems Exposure to production ML systems and MLOps practices Academic or industry research experience in NLP, information retrieval, search, or generative AI Experience ...

year. In addition, ChEBI underpins many of the key global biological databases upon which researchers in the biosciences are increasingly reliant such as Gene Ontology (GO), Rhea, UniProtKB, IEDB, Reactome, MetaboLights, SwissLipids, and BioModels. The ChEBI database and ontology is a fundamental component of the global bioscience infrastructure, recognised … Chemical Biology Services team leader, the job responsibilities will include: Curation of entries into ChEBI, paying particular attention to chemical structures and the ChEBI ontology, to ensure the delivery of high quality data Monitoring ChEBIs monthly release process and liaising with technical/software colleagues if problems arise. Monitoring daily ...

year. In addition, ChEBI underpins many of the key global biological databases upon which researchers in the biosciences are increasingly reliant such as Gene Ontology (GO), Rhea, UniProtKB, IEDB, Reactome, MetaboLights, SwissLipids, and BioModels. The ChEBI database and ontology is a fundamental component of the global bioscience infrastructure, recognised … Chemical Biology Services team leader, the job responsibilities will include: Curation of entries into ChEBI, paying particular attention to chemical structures and the ChEBI ontology, to ensure the delivery of high quality data Monitoring ChEBIs monthly release process and liaising with technical/software colleagues if problems arise. Monitoring daily ...

frameworks and contribute recommendations for experimentation and adoption.Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts.Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows.Search, Retrieval & RAG SystemsDesign, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.Contribute … assistants, agentic workflows, or conversational AI applicationsExperience working on search, ranking, recommendation, or retrieval systemsFamiliarity with scientific, biomedical, or scholarly datasetsExperience with knowledge graphs, ontologies, or semantic enrichment systemsExposure to production ML systems and MLOps practicesAcademic or industry research experience in NLP, information retrieval, search, or generative AIExperience working ...

years we expect this line to evolve from batch data model packs into a real-time streaming analytics engine, built on a canonical ontology of digital journeys that both humans and AI agents can reason over.Reporting to the CPO, this is a senior individual-contributor role, built for someone … retention, and growth across marketing and customer success. That spans three frontiers: evolving our data model packs beyond batch into streaming computation, defining the ontology of digital journeys (the entities, events, and relationships that describe how people and agents move through digital products), and connecting Snowplow's semantics to open ...