Ontology Lead

We are looking for an Ontology Lead to define and implement enterprise knowledge models that serve as the semantic foundation for AI Analytics and Generative AI solutions. The ideal candidate will lead the design of ontologies taxonomies and knowledge graphs enabling organizations to create trusted connected and machine-understandable representations of business data across domains.

Key Responsibilities

Design and own enterprise ontologies taxonomies semantic models and knowledge graph architectures.
Partner with business stakeholders and domain experts to model complex business concepts processes and relationships.
Define standards governance frameworks and best practices for ontology and semantic model development.
Architect and oversee the implementation of knowledge graphs on enterprise graph platforms.
Design integrations between ontologies knowledge graphs enterprise data platforms and operational systems.
Enable AI and Generative AI use cases through semantic search GraphRAG metadata frameworks and LLM grounding.
Collaborate with data engineering teams to establish ingestion transformation and synchronization pipelines for knowledge graphs.
Drive semantic consistency across business domains and establish a common enterprise vocabulary.
Review and guide implementation teams on ontology modeling graph design and semantic architecture best practices.
Present architecture recommendations trade-offs and business value propositions to client and executive stakeholders.

Required Qualifications & Experience

Bachelors or Masters degree in Computer Science Information Systems Data Science Knowledge Engineering or a related field.
9-12 years of experience in Knowledge Architecture Data Architecture Data Engineering or Enterprise Data Management.
Hands-on experience designing and implementing enterprise ontologies taxonomies or knowledge graphs.
Experience delivering end-to-end semantic modeling or knowledge graph implementations in production environments.
Strong understanding of data modeling methodologies enterprise data architecture and metadata management.
Experience working directly with global enterprise stakeholders in consulting or client-facing environments.
Excellent communication stakeholder management and problem-solving skills.

Technical Skills & Technologies

Graph Platforms: Neo4j Stardog GraphDB Amazon Neptune TigerGraph.
Semantic Technologies: RDF OWL SPARQL SKOS Knowledge Representation.
Knowledge Graphs: Property Graphs Triple Stores Graph Modeling.
GenAI & AI: GraphRAG RAG Semantic Search LLM Grounding Agentic AI Concepts.
Data Platforms: Databricks Snowflake Spark Delta Lake.
Data Integration: Airflow ETL/ELT Frameworks APIs.
Databases: PostgreSQL SQL Server NoSQL Databases.
Cloud Platforms: Azure AWS GCP.
Programming: Python SQL.
Metadata & Governance: Enterprise Metadata Management Business Glossaries Data Catalogs.

Behavioral Competencies

Strong systems thinking and conceptual modeling abilities.
Excellent stakeholder management and consulting skills.
Ability to translate business concepts into scalable semantic frameworks.
Strong architectural decision-making and problem-solving capabilities.
High ownership accountability and attention to detail.
Ability to mentor teams and drive adoption of semantic best practices.

Nice-to-Have

Experience with GraphRAG semantic search and enterprise GenAI applications.
Exposure to graph algorithms Graph ML or Graph Neural Networks (GNNs).
Experience with Data Vault 2.0 Kimball canonical data models or enterprise information architecture.
Knowledge of data quality ontology validation and graph governance frameworks.
Experience in Pharma Manufacturing Retail CPG or Healthcare industries.

Being a Mathemagician

Embody MathCos culture and way of working.
Demonstrate ownership and strive for excellence in delivering results.
Actively engage and contribute to initiatives fostering company growth.
Support diversity and

Required Experience:

IC