Decision Science Manager- Data Ontology

ValueMomentum; Hyderabad; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Value Momentum seeks an experienced Data Ontologist to design and maintain enterprise ontologies, taxonomies, and semantic models for Property & Casualty insurance. You will standardize data definitions across policy, claims, underwriting, broker, and customer data to enable AI use cases, knowledge graphs, and data products.

Collaborate with data governance, AI teams, and business SMEs to ensure governance, reusability, and scalable semantic assets across the analytics center.

Qualifications

• 8+ years in Data Management, Data Architecture, or Knowledge Management.
• 3+ years of Experience with Knowledge Graphs and semantic technologies.
• Understanding of RDF, OWL, SKOS, SPARQL (preferred).
• Experience with Collibra, Purview, Unity Catalog, or OpenMetadata.

Responsibilities

• Design and maintain enterprise ontologies for P&C insurance business domains.
• Develop business taxonomies, controlled vocabularies, and semantic models.
• Build and manage Knowledge Graphs representing relationships across business entities.
• Define canonical business models aligned with enterprise standards.
• Collaborate with business SMEs, data architects, and AI teams to standardize business definitions.

Skills

Data Management

Data Architecture

Knowledge Management

Knowledge Graphs

Semantic Technologies

RDF/OWL/SPARQL

AI / RAG

Tools

Collibra

Purview

Unity Catalog

OpenMetadata

Databricks

Snowflake

Azure

AWS

Job description

Designation: Decision Science Architect/Data Ontologist

Advanced Analytics Center at Value Momentum:

At Value Momentum, we've strategically established an Advanced Analytics Center in to bolster our AI and Analytics capabilities in the Property & Casualty (P&C) Insurance sector. This unit is dedicated towards revolutionizing the P&C Insurance with cutting-edge AI and analytics solutions. Advanced Analytics Center plays a pivotal role in company's overall IT consulting and services talent strategy, with a focus on capability development, fostering reusability, and stimulating experimentation and innovation.

Our work environment is dynamic, intellectually stimulating, and seamlessly combines capability development with service delivery. Comprising a diverse team of data scientists, analysts, and consultants specializing in analytics, we offer a distinctive blend of industry expertise, AI proficiency, and top-tier technologies. By collaborating with business verticals, engineering centers, and our clients, Advanced Analytics team delivers state-of-the-art AI/analytics solutions across the P&C value chain - Product/Underwriting, Claims, Distribution, and Enterprise IT.

About the Role

We are looking for an experienced Data Ontologist to build and maintain enterprise business ontologies, taxonomies, and semantic models for Property & Casualty (P&C) Insurance. The role will help establish a common business language across policy, claims, underwriting, broker, customer, and financial data while enabling AI, Knowledge Graphs, and Data Products.

Key Responsibilities

• Design and maintain enterprise ontologies for P&C insurance business domains.
• Develop business taxonomies, controlled vocabularies, and semantic models.
• Build and manage Knowledge Graphs representing relationships across business entities.
• Define canonical business models aligned with enterprise standards.
• Collaborate with business SMEs, data architects, and AI teams to standardize business definitions.
• Create semantic mappings across multiple source systems.
• Support AI use cases including RAG, Enterprise Search, and Agentic AI.
• Develop business glossaries and metadata standards.
• Ensure consistency, governance, and version control of ontology assets.
• Work closely with Data Governance and Data Product teams.

Required Skills

• 8+ years in Data Management, Data Architecture, or Knowledge Management.
• Strong understanding of P&C Insurance (Claims, Policy, Underwriting, Broker, Customer).
• 3 + years of Experience with Knowledge Graphs and semantic technologies.
• Understanding of RDF, OWL, SKOS, SPARQL (preferred).
• Experience with Collibra, Purview, Unity Catalog, or OpenMetadata.
• Familiarity with Databricks, Snowflake, Azure, or AWS.
• Knowledge of AI, RAG, and LLM-based applications is an advantage.

Preferred Qualifications

• Experience with ACORD standards.
• Exposure to Graph Databases (Neo4j, Amazon Neptune, GraphDB).
• Understanding of Data Governance and Master Data Management.

Success Measures

• Improved AI search and retrieval accuracy.
• Better data consistency and governance.