::URGENT OPENING:: Senior Data Modeler / Ontologist
221 B Baker ST · Mumbai, India
FULL TIME
Job Description
No Of Positions: 02 Work mode: Hybrid (2 days work from Apexon office is mandate) Work Location: Bangalore, Hyderabad, Chennai, Mumbai, Ahmedabad, Pune and Coimbatore. Notice: Immediate Experience: 10 to 14 Years.
Please find below the JD:
Role Summary We are seeking an experienced Data Ontologist to design, develop, and govern enterprise knowledge models that enable semantic interoperability, AI-driven insights, data discovery, and intelligent automation. The ideal candidate will have strong expertise in ontology modeling, knowledge graphs, metadata management, semantic technologies, and deep domain knowledge in either Insurance (Claims, Policy Administration, Underwriting) or Financial Services. The candidate will work closely with business SMEs, data architects, AI/ML teams, and data engineers to establish enterprise ontologies that standardize business concepts, relationships, and terminology across the organization.
Key Responsibilities Design, develop, and maintain enterprise ontologies, taxonomies, and semantic data models. Build and manage domain-specific knowledge graphs for Insurance or Financial Services. Define business entities, relationships, hierarchies, vocabularies, and controlled terminologies. Collaborate with business stakeholders to translate business concepts into reusable ontology models. Align ontology models with enterprise data architecture, data governance, and metadata standards. Map structured and unstructured data into semantic models. Support AI, GenAI, NLP, and RAG initiatives through well-defined semantic knowledge structures. Develop ontology governance processes, versioning standards, and lifecycle management. Create semantic mappings across multiple source systems. Partner with data engineering teams to integrate ontologies with enterprise data platforms. Support data catalog, metadata management, master data management (MDM), and business glossary initiatives. Ensure semantic consistency across enterprise reporting and analytics platforms. Document ontology design principles, modeling standards, and reusable semantic assets. Drive adoption of enterprise semantic standards across multiple business domains.
Required Skills Ontology & Semantic Technologies OWL RDF RDFS SKOS SPARQL SHACL Knowledge Graphs Linked Data Semantic Web technologies Taxonomy Management Business Glossary Metadata Management Data Technologies SQL Graph Databases (Neo4j, Amazon Neptune, Stardog, GraphDB) Data Modeling Metadata Repositories MDM Data Governance Data Lineage Cloud & AI Azure / AWS / GCP Microsoft Purview / Collibra / Informatica GenAI LLMs Retrieval-Augmented Generation (RAG) NLP Vector Databases (preferred) Domain Expertise (Mandatory)
Candidates must possess strong business knowledge in at least one of the following domains: Insurance Experience in one or more of: Claims Management First Notice of Loss (FNOL) Claims Adjudication Policy Administration Underwriting Coverage Premium Rating Policy Lifecycle Reinsurance Fraud Detection Loss Reserves Customer Servicing OR Financial Services Experience in one or more of: Banking Lending Mortgage Capital Markets Payments Wealth Management Financial Risk Regulatory Reporting AML/KYC Customer 360 Treasury Financial Products
Preferred Qualifications Experience building enterprise knowledge graphs. Exposure to ontology-driven AI applications. Experience integrating ontologies with data catalogs and governance platforms. Understanding of FAIR data principles. Knowledge of ISO, ACORD (Insurance), FIBO (Financial Industry Business Ontology), or other industry ontology standards. Familiarity with Python, Java, or Scala for ontology automation is desirable. Experience working in Agile delivery environments. Education Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, or a related field.
Nice to Have Certified Data Management Professional (CDMP) TOGAF Collibra Certification Neo4j Certification Stardog Certification Microsoft Purview Certification Cloud Certifications (Azure/AWS/GCP)
Key Competencies Enterprise Data Modeling Semantic Modeling Knowledge Graph Design Ontology Engineering Business Process Analysis Data Governance Metadata Management Stakeholder Management Analytical Thinking Excellent Communication Skills Success Measures High-quality enterprise ontology models delivered. Improved semantic interoperability across business systems. Increased data discoverability and reuse. Enhanced AI/LLM performance through semantic enrichment. Standardized enterprise vocabulary across Insurance or Financial Services. Strong governance and adoption of ontology standards.
Please find below the JD:
Role Summary We are seeking an experienced Data Ontologist to design, develop, and govern enterprise knowledge models that enable semantic interoperability, AI-driven insights, data discovery, and intelligent automation. The ideal candidate will have strong expertise in ontology modeling, knowledge graphs, metadata management, semantic technologies, and deep domain knowledge in either Insurance (Claims, Policy Administration, Underwriting) or Financial Services. The candidate will work closely with business SMEs, data architects, AI/ML teams, and data engineers to establish enterprise ontologies that standardize business concepts, relationships, and terminology across the organization.
Key Responsibilities Design, develop, and maintain enterprise ontologies, taxonomies, and semantic data models. Build and manage domain-specific knowledge graphs for Insurance or Financial Services. Define business entities, relationships, hierarchies, vocabularies, and controlled terminologies. Collaborate with business stakeholders to translate business concepts into reusable ontology models. Align ontology models with enterprise data architecture, data governance, and metadata standards. Map structured and unstructured data into semantic models. Support AI, GenAI, NLP, and RAG initiatives through well-defined semantic knowledge structures. Develop ontology governance processes, versioning standards, and lifecycle management. Create semantic mappings across multiple source systems. Partner with data engineering teams to integrate ontologies with enterprise data platforms. Support data catalog, metadata management, master data management (MDM), and business glossary initiatives. Ensure semantic consistency across enterprise reporting and analytics platforms. Document ontology design principles, modeling standards, and reusable semantic assets. Drive adoption of enterprise semantic standards across multiple business domains.
Required Skills Ontology & Semantic Technologies OWL RDF RDFS SKOS SPARQL SHACL Knowledge Graphs Linked Data Semantic Web technologies Taxonomy Management Business Glossary Metadata Management Data Technologies SQL Graph Databases (Neo4j, Amazon Neptune, Stardog, GraphDB) Data Modeling Metadata Repositories MDM Data Governance Data Lineage Cloud & AI Azure / AWS / GCP Microsoft Purview / Collibra / Informatica GenAI LLMs Retrieval-Augmented Generation (RAG) NLP Vector Databases (preferred) Domain Expertise (Mandatory)
Candidates must possess strong business knowledge in at least one of the following domains: Insurance Experience in one or more of: Claims Management First Notice of Loss (FNOL) Claims Adjudication Policy Administration Underwriting Coverage Premium Rating Policy Lifecycle Reinsurance Fraud Detection Loss Reserves Customer Servicing OR Financial Services Experience in one or more of: Banking Lending Mortgage Capital Markets Payments Wealth Management Financial Risk Regulatory Reporting AML/KYC Customer 360 Treasury Financial Products
Preferred Qualifications Experience building enterprise knowledge graphs. Exposure to ontology-driven AI applications. Experience integrating ontologies with data catalogs and governance platforms. Understanding of FAIR data principles. Knowledge of ISO, ACORD (Insurance), FIBO (Financial Industry Business Ontology), or other industry ontology standards. Familiarity with Python, Java, or Scala for ontology automation is desirable. Experience working in Agile delivery environments. Education Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, or a related field.
Nice to Have Certified Data Management Professional (CDMP) TOGAF Collibra Certification Neo4j Certification Stardog Certification Microsoft Purview Certification Cloud Certifications (Azure/AWS/GCP)
Key Competencies Enterprise Data Modeling Semantic Modeling Knowledge Graph Design Ontology Engineering Business Process Analysis Data Governance Metadata Management Stakeholder Management Analytical Thinking Excellent Communication Skills Success Measures High-quality enterprise ontology models delivered. Improved semantic interoperability across business systems. Increased data discoverability and reuse. Enhanced AI/LLM performance through semantic enrichment. Standardized enterprise vocabulary across Insurance or Financial Services. Strong governance and adoption of ontology standards.
Details
| Company | 221 B Baker ST |
| Location | Mumbai, India |
| Type | FULL TIME |
| Niche | general |