Knowledge Modeler / Ontologist Manager

Accenture•St. Louis, MO

1d•$80,400 - $293,800•Hybrid

About The Position

Accenture is seeking an experienced Knowledge Modeler / Ontologist to contribute to domain ontology design, governance, and delivery for enterprise knowledge graph initiatives. Working collaboratively within a team and under the guidance of an ontology governance framework, this role bridges business stakeholders, data engineering, and AI/ML teams – translating complex business domains into rigorous, standards-compliant semantic models that power intelligent applications.

Requirements

Minimum 5 years of hands-on experience in ontology engineering, knowledge modeling, or a closely related semantic web discipline
Minimum 5 years demonstrable experience delivering domain ontologies in an enterprise or consulting context
Bachelor’s in Information Science, Computer Science, Library Science, Linguistics, Philosophy, or a related field
Proficiency in OWL 2, RDF, RDFS, SKOS, SHACL, and SPARQL for building and validating semantic models
Working knowledge of W3C standards and best practices for linked data and knowledge representation
Experience designing and querying knowledge graphs using tools such as GraphDB, Stardog, or Neo4j
Hands-on experience with ontology authoring tools such as Protégé or Ontotext
Familiarity with R2RML or RML for mapping relational or semi-structured sources into semantic models
Ability to formulate and use competency questions to scope, validate, and iterate on ontological models
Familiarity with upper ontologies such as BFO, DOLCE, or schema.org and their role in interoperability
Ability to translate complex technical concepts into business-friendly language and engage effectively with both technical and non-technical stakeholders

Nice To Haves

Master’s degree in Information Science, Computer Science, Library Science, Linguistics, Philosophy, or a related field — or equivalent practical experience
Experience working in Agile or iterative delivery environments preferred

Responsibilities

Lead the full ontology lifecycle supporting a defined project scope: requirements gathering, conceptual modeling, formal specification (OWL 2, RDFS, SKOS), validation, and deployment
Design T-Box (schema) structures and contribute to A-Box (instance) hydration patterns across structured and unstructured data sources
Apply and uphold established naming conventions, URI strategies, and modular ontology architecture principles
Apply advanced modeling patterns where appropriate (e.g., reification, n-ary relations, punning) in consultation with senior team members
Create and evolve ontologies, taxonomies, and vocabularies using standards including OWL, RDF, RDFS, and SKOS
Map traditional data structures (e.g., relational databases) into semantic frameworks
Build and maintain knowledge graphs to support reasoning, discovery, and advanced analytics
Ensure models align with business goals, regulatory requirements, and data governance practices
Coach the business (SMEs and stakeholders) in developing and validating competency questions to guide and test ontology scope and correctness
Maintain awareness of relevant upper ontologies (e.g., BFO, schema.org) and apply alignment patterns as appropriate
Facilitate business SME workshops with BA support to elicit domain concepts, relationships, and competency questions
Translate ambiguous business language into precise, machine-readable semantics
Communicate modeling decisions to non-technical stakeholders in accessible terms
Support feedback loops between business validation and ontology iteration
Apply ontology governance standards: version control, change management, and quality gates (W3C compliance, SHACL/ShEx validation)
Define and enforce Definition of Done criteria for ontology deliverables in collaboration with the senior team
Apply R2RML / RML mapping strategies for structured data integration
Collaborate with Entity Extraction / NLP teams on ontology-guided information extraction from unstructured sources
Collaborate with knowledge graph hydration, testing, and validation against competency questions
Work effectively within cross-functional delivery teams spanning Data Engineering, AI/ML, Product, and Business SMEs
Collaborate with and support junior team members, sharing knowledge and modeling approaches
Meet delivery timelines and proactively flag dependencies or risks to senior ontologist or project lead
Provide accurate and achievable estimates for ontology-related work and contribute to roadmap planning as part of the broader project scope