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 solid 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.

📌 ::URGENT OPENING:: Senior Data Modeler / Ontologist (Hyderabad)
🏢 221 B Baker ST
📍 Hyderabad