Job description
At Randstad Digital, we are looking for a Taxonomist/KM Manager to join our team. This is a contract position based in Austin, Texas with work hours from 8AM to 5PM.
Preferred Qualifications:
- Experience implementing or governing taxonomy/ontology programs in financial services, healthcare, or large-scale enterprise environments
- Familiarity with AI-adjacent knowledge representation - including knowledge graph integration with LLMs, RAG pipelines, or semantic search architectures
- Experience with localization or multilingual taxonomy design across multiple locales
- Exposure to Agile or DevSecOps practices in a data engineering or platform context
- Track record of building taxonomy/ontology programs from greenfield - defining scope, tooling, governance, and stakeholder buy-in
- Experience with authority control, entity resolution, or identity management
Core Expertise Requirements:
- 5-7+ years in taxonomy design ontology engineering, knowledge management, or information architecture
- Demonstrated experience designing and governing enterprise-scale taxonomies and controlled vocabularies
- Proficiency with Semantic Web standards: RDF/RDFS, OWL, SKOS, SPARQL, SHACL
- Experience developing or contributing to knowledge graphs or ontology-backed data models
- Familiarity with metadata schema standards (Dublin Core, Schema.org, BIBFRAME, or domain equivalents)
- Background in data modeling methodologies (conceptual, logical, physical; 3NF, Data Vault, XML Schema)
- Experience with industry ontology frameworks relevant to the domain (e.g., FIBO for financial services, ISO 20022)
Education:
Bachelor's or Master's degree in Library & Information Science, Computer Science, Linguistics, Information Systems, or a related field
Equivalent professional experience in knowledge engineering or taxonomy management accepted
Proficiency Needed:
Tools & Technologies
Ontology & Taxonomy Management
- PoolParty Semantic Suite
- Protégé
- TopBraid Composer / TopQuadrant products
- Palantir Foundry
Semantic Web & Data Standards
- RDF / RDFS / OWL / SKOS
- SPARQL, SHACL, SPIN
- Schema.org, Dublin Core, BIBFRAME
- FIBO, ISO 20022 (financial domain)
Data & Engineering
(Good to have - not needed per se)
- Python, R, or equivalent scripting
- SQL / GraphQL
- GraphDB or equivalent triplestore
- Git / CI-CD pipelines
- JSON / structured data formats
Content & Knowledge Platforms
(Good to have - not needed per se)
- CMS and DAM platforms
- Enterprise knowledge management systems
Responsibilities:
- Design, build, and maintain enterprise taxonomies, controlled vocabularies, and hierarchical classification systems across content and data domains
- Conduct content inventories, gap analyses, and requirements gathering to inform taxonomy structure and scope
- Define vocabulary standards, preferred/alternate terms, broader/narrower relationships, and cross-references aligned with industry standards (ANSI/NISO Z39.19, ISO 25964)
- Develop and enforce metadata schemas and tagging guidelines to support consistent content classification across platforms
- Train stakeholders and content teams in taxonomy application and metadata best practices
- Design and implement ontologies using Semantic Web standards (RDF/RDFS, OWL, SKOS) to model domain knowledge and entity relationships
- Develop and maintain knowledge graphs that integrate taxonomies, ontologies, and instance data to support AI, search, and analytics use cases
- Create, validate, and govern ontology change requests; own ontology tooling requirements and process improvements
- Perform authority control and entity management for organizational entities (people, organizations, products, concepts)
- Apply validation and reasoning standards (SHACL, SPIN) to ensure ontology integrity and consistency
- Define and evolve the organization's knowledge architecture - the structures, systems, and processes that enable knowledge creation, classification, retrieval, and reuse
- Partner with data management, search, product management, ML, and engineering teams to implement standardized vocabularies and semantic models in data consumption experiences
- Map unstructured data to structured semantic models that integrate with data infrastructure and AI/ML pipelines
- Establish metadata standards, modeling guidelines, and data lineage documentation in collaboration with data governance and engineering teams
- Support knowledge organization workshops to align enterprise taxonomy and data models across business units
- Develop and manage taxonomy and ontology governance processes, including change management, review cycles, and versioning
- Perform regular audits of information architecture to maintain compliance and optimize classification performance
- Write process documentation, governance standards, and training materials for taxonomy and metadata programs
- Serve as a cross-functional SME, bridging taxonomy design with data engineering, content strategy, and product teams
- Communicate ontology and taxonomy design decisions to both technical and non-technical audiences, including senior leadership
Qualifications:
- Bachelor's or Master's degree in Library & Information Science, Computer Science, Linguistics, Information Systems, or a related field
- Equivalent professional experience in knowledge engineering or taxonomy management accepted
