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About Apexon
Apexon is a digital-first technology services firm specializing in accelerating business transformation and delivering human-centric digital experiences. We help customers outperform their competition through speed and innovation, wherever they are in the digital lifecycle.
Apexon brings together core competencies in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering, and UX — combined with deep expertise in BFSI, healthcare, and life sciences — to help businesses capitalize on the opportunities digital offers.
Backed by Goldman Sachs Asset Management and Everstone Capital, Apexon has a global presence of 15 offices (and 10 delivery centers) across four continents.
We enable #HumanFirstDigital
Role Summary
We are seeking an experienced Data Modeler with Data Ontology experience 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, and semantic technologies — along with deep domain knowledge in either Insurance (Claims, Policy Administration, Underwriting) or Financial Services.
You 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
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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 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 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 (desirable)
- Experience working in Agile delivery environments
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Education
Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, or a related field.
Nice to Have (Certifications)
- 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
Our Commitment to Diversity & Inclusion
Apexon has been Certified™ by Great Place To Work®, the global authority on workplace culture, in each of the four regions in which it operates: USA (7th time in 2026), India (10th consecutive time in 2026), UK (4th time in 2026), and Mexico (2nd time in 2026).
Apexon is committed to being an equal opportunity employer and promoting diversity in the workplace. We take affirmative action to ensure equal employment opportunity for all qualified individuals. Apexon strictly prohibits discrimination and harassment of any kind and provides equal employment opportunities to employees and applicants without regard to gender, race, color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law.
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