Key Responsibilities and Required Skills for Taxonomist

🎯 Role Definition

A Taxonomist is a subject-matter expert who designs, implements, and governs structured classification systems (taxonomies, ontologies, controlled vocabularies, and metadata schemas) that improve content discoverability, search relevance, data interoperability, and enterprise knowledge organization. The role combines information architecture, metadata modeling, content strategy, and stakeholder management to deliver scalable, reusable classification solutions across CMS, search platforms, data lakes, and knowledge graphs.

Key responsibilities include taxonomy lifecycle design and maintenance, metadata governance and standards enforcement, content tagging strategy and implementation, search and discovery optimization (faceted navigation, thesauri, synonyms), and cross-functional collaboration with product, engineering, content, legal, and analytics teams.

📈 Career Progression

Typical Career Path

Entry Point From:

Junior Taxonomist, Metadata Specialist, or Content Analyst
Librarian / Library & Information Science (MLIS) roles
Content strategist, SEO specialist, or information architecture junior roles

Advancement To:

Senior Taxonomist / Lead Taxonomist
Information Architect / Head of Taxonomy & Metadata
Knowledge Graph / Ontology Lead
Director of Content Strategy or Data Governance

Lateral Moves:

Search Relevance Engineer
Content Strategy Lead
Data Governance or Metadata Manager

Core Responsibilities

Primary Functions

Lead the end-to-end design, development, and continuous improvement of enterprise taxonomies, ontologies, controlled vocabularies, and classification schemes to support search, navigation, personalization, analytics, and content reuse across digital properties.
Conduct comprehensive content audits and inventories (including CMS exports, web crawls, and analytics logs) to identify content types, metadata gaps, and taxonomy alignment opportunities that inform classification models and tagging requirements.
Define and maintain metadata schemas, field-level definitions, data types, and required vs. optional attributes to ensure consistent, machine-actionable metadata across systems and repositories.
Build and document taxonomy governance frameworks, including versioning policies, change control workflows, editorial guidelines, stakeholder sign-off processes, and service-level agreements (SLAs) for taxonomy requests and updates.
Create, curate, and maintain hierarchical and faceted taxonomies, synonym lists, stopword lists, crosswalks to external vocabularies, and mappings to authoritative sources (e.g., industry taxonomies, Library of Congress, product catalogs).
Translate business requirements and user research into taxonomy models that improve findability, reduce content duplication, and enhance conversion funnels for e-commerce, knowledge bases, support portals, and intranets.
Implement and manage taxonomy mapping and alignment efforts between disparate systems (CMS, PIM, DAM, e-commerce platform, data warehouse, and knowledge graph) to enable consistent tagging and downstream analytics.
Design and execute scalable automated and hybrid (machine + human) tagging strategies using rules-based mapping, supervised ML classifiers, NLP entity extraction, and manual curation workflows.
Collaborate with search, UX, and engineering teams to apply taxonomy logic to search relevance tuning, faceted navigation, autocomplete suggestions, and query expansion strategies to improve user search success rates.
Develop formal taxonomy documentation, style guides, editorial glossaries, business definitions, and training materials to onboard content teams and subject-matter experts to controlled-vocabulary practices.
Serve as the subject-matter expert in stakeholder workshops and cross-functional working sessions to align taxonomy decisions with product roadmaps, content operations, legal requirements, and analytics goals.
Run taxonomy and metadata QA processes, including spot checks, automated validation scripts, sampling strategies, and reconciliation of tagging discrepancies to maintain high data quality and governance standards.
Analyze content performance and search analytics (click-through rates, zero-results searches, query reformulations) to prioritize taxonomy enhancements and to measure the impact of taxonomy changes on KPIs.
Manage taxonomy lifecycle activities including release planning, regression testing, change deployment, rollback procedures, and communication of changes to impacted teams and downstream systems.
Build taxonomy integrations and mapping artefacts (CSV, JSON-LD, SKOS, RDF, OWL) for programmatic ingestion by CMS, DAM, PIM, e-commerce platforms, or knowledge graph pipelines.
Support legal, compliance, and localization teams in implementing taxonomies that comply with regulatory requirements and that support localization/translation workflows for multilingual taxonomies.
Create and maintain mapping between taxonomy facets and analytics dimensions to enable consistent reporting, dashboards, and insights from BI tools and data warehouses.
Mentor and coach junior taxonomy, metadata, and content operations staff; run internal training sessions and contribute to a center-of-excellence for information organization practices.
Evaluate and recommend taxonomy and metadata tooling (taxonomy management platforms, metadata repositories, auto-tagging services, knowledge graph technologies, Elasticsearch / Solr integrations) and manage vendor relationships and PoCs.
Design and oversee controlled vocabulary expansion processes (term addition, deprecation, synonyms, broader/narrower relationships) guided by data, stakeholder input, and user research.
Partner with data engineering and architects to model taxonomies for semantic interoperability (RDF triples, entity graphs), and to ensure taxonomy artifacts are discoverable and consumable via APIs and services.
Facilitate user testing sessions, card sorts, tree tests, and usability research to validate taxonomy structures, labels, and navigation flows with real users and iterate based on feedback.
Establish and implement taxonomy KPIs and SLAs (accuracy of auto-tagging, coverage, tag consistency, search success, time-to-implement requests) and report outcomes to leadership to demonstrate ROI.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.
Assist content teams with onboarding to taxonomy tools, tagging best practices, and ad-hoc taxonomy-related content triage.
Help prepare executive summaries, stakeholder updates, and cross-functional readiness plans when taxonomy changes impact product launches.

Required Skills & Competencies

Hard Skills (Technical)

Taxonomy design and management: hierarchical taxonomies, faceted classification, thesauri, controlled vocabularies, and synonym handling.
Metadata modeling: schema design, field definitions, data types, required/optional fields, and metadata interoperability.
Ontology engineering basics: building and maintaining SKOS, RDF, and OWL artifacts and mapping to knowledge graphs.
Information architecture and content modeling experience for CMS, PIM, DAM, or e-commerce platforms.
Search platform knowledge: Elasticsearch, Solr, or cloud search services (AWS OpenSearch, Algolia) to apply taxonomy-driven relevance tuning and faceting.
Auto-tagging and NLP tools: experience with text classification, named-entity recognition, rules-based taggers, and integration of ML/NLP services.
Data and analytics literacy: ability to analyze search logs, query analytics, and content performance metrics using SQL, Google Analytics, or BI tools.
Taxonomy tooling and export formats: familiarity with taxonomy management platforms (PoolParty, Smartlogic, TermWeb, TopBraid), CSV/JSON/JSON-LD, and SKOS/RDF exports.
CMS and content workflows familiarity: practical experience integrating taxonomy with Drupal, WordPress, Adobe Experience Manager, Sitecore, or commercial CMS.
Data governance and lifecycle practices: version control, change management, QA testing, and API-driven taxonomy delivery.
Mapping and integration skills: ability to create crosswalks between taxonomies, external vocabularies, and product/category data sources.
Multilingual taxonomy and localization experience: term translation workflows, locale-specific hierarchies, and internationalization best practices.

Soft Skills

Strong stakeholder management: build consensus across product, engineering, content, SEO, legal, and business teams.
Excellent written and verbal communication: produce clear taxonomy documentation, training materials, and executive reporting.
Analytical problem-solving: use quantitative and qualitative evidence to prioritize taxonomy updates and measure impact.
Detail-oriented and methodical: maintain high quality of metadata and taxonomy artifacts across large content inventories.
Facilitation and workshop skills: run card sorts, tree tests, and cross-functional design sessions to validate taxonomy decisions.
Project and time management: balance concurrent taxonomy projects, roadmap planning, and support requests with clear SLAs.
Adaptability: work in agile environments and adjust taxonomy approaches in response to new product needs or technical constraints.
Coaching and mentoring: upskill content teams and junior taxonomy practitioners through training and hands-on guidance.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Library & Information Science, Information Science, Computer Science, Linguistics, Knowledge Management, Data Science, or related field.

Preferred Education:

Master's degree such as MLIS (Master of Library and Information Science), MS in Information Science, Knowledge Organization, Computational Linguistics, or related advanced degree.

Relevant Fields of Study:

Library and Information Science (MLIS)
Information Architecture / UX
Computer Science / Data Science
Linguistics / Computational Linguistics
Knowledge Management / Semantic Web

Experience Requirements

Typical Experience Range:

3–7 years working in taxonomy, metadata, information architecture, content strategy, or related roles. Senior or lead roles often require 7+ years.

Preferred:

Demonstrated experience designing and governing enterprise taxonomies, working with search platforms and CMS integrations, and running cross-functional taxonomy initiatives; experience with SKOS/RDF/OWL and knowledge graph projects is a strong plus.
Proven track record of improving search relevance or content findability via taxonomy-driven projects and quantifying impact with analytics.