1 to 25 of 153 Ontologies Jobs

drive for learning!As a member of our team You will work on a team with software engineers and data scientists to build ontologies and capabilities for applied national security mission needs. You will engage stakeholders to determine ontology requirements. You will work with subject matter experts to craft ontology … degree fields may include Philosophy, Computer Science, Cognitive Science, Public/Social Policy, Mathematics, Logic, or Linguistics. Are proficient with any of the following: Ontology Web Language (OWL), Resource Description Framework Schema (RDFs), and Resource Description Framework (RDF) Have experience crafting SPARQL queries Have experience building domain ontologies Are familiar ...

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 ...

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 ...

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 ...

constraints* Ensure 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 understanding* Help ensure AI use cases comply with **data privacy, security and regulatory requirements** (e.g. GDPR, sector specific ...

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 ...

streaming responses, async inference jobs, and robust error/retry semantics. Palantir Foundry Integration Work with Palantir Foundry to build and maintain data pipelines, ontologies, and integrations that connect backend services to Foundry-based analytics and workflows. Leverage Foundry's APIs and tooling to support data modelling, transformation, and secure ...

streaming responses, async inference jobs, and robust error/retry semantics. Palantir Foundry Integration Work with Palantir Foundry to build and maintain data pipelines, ontologies, and integrations that connect backend services to Foundry-based analytics and workflows. Leverage Foundry's APIs and tooling to support data modelling, transformation, and secure ...

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 ...

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 ...

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 ...

sync with reality has consequences. Previous experience in AI drug discovery is a genuine differentiator for us. Interest in semantic technologies (graph databases, ontologies) or modern data stack. Experience enabling analytics teams by building data models for BI tools and dashboards. Familiarity with Infrastructure as Code (AWS CDK or Terraform ...

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 ...

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 ...

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 ...

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 ...

Readiness – quality, lineage, observability, catalog, access controls, PII, retention, AI data governance. Provide business context to a Semantic & Context Architecture with metrics layer, business ontology, entity relationships, metadata, knowledge graphs/semantic models. Scale the team – build, mentor, motivate and lead high-performance team across Data Engineering, Analytics Engineering ...