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Senior Taxonomist

Job in Seattle, King County, Washington, 98127, USA
Listing for: GEICO
Full Time position
Listed on 2026-01-10
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below

Overview

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge:
Great Company, Great Culture, Great Rewards and Great Careers.

We are seeking an experienced and technically proficient Taxonomist to join our Enterprise Data team. This role is pivotal in structuring the data and language that powers our machine learning (ML) models, generative AI (GenAI) applications, NLP use cases, and enterprise knowledge graphs. You will partner closely with Engineering, Product, Business owners and AI teams to ensure content is structured, organized, and compliant across its lifecycle.

The ideal candidate will bridge the gap between business semantics and machine requirements, ensuring data is clean, consistent, and logically classified. This role will be critical in driving a common understanding and language for businesses across all domains. This individual will be part of a team responsible for leveraging semantic platforms and models to accelerate the implementation of context management and agentic AI to address critical business priorities for the data and AI teams.

Location

This hybrid role requires on-site presence three days per week at one of GEICO’s office locations:
Bethesda, MD;
Palo Alto, CA;
Dallas, TX;
Seattle, WA or New York, NY.

Key Responsibilities
  • Lead the development and maintenance of enterprise-wide taxonomies, controlled vocabulary, and metadata frameworks for human use and AI/ML and data applications.
  • Partner with Data Scientists to structure training datasets, ensuring labels and categories are unambiguous and consistent across massive data volumes.
  • Partner with Engineering teams to enhance internal and external search powered by taxonomy and metadata.
  • Establish and document clear standards for data annotation and labeling, minimizing variance and noise in training data.
  • Collaborate with subject matter experts, domain owners and enterprise ontologists to establish governance processes for taxonomy updates, versioning and sun setting; ensure changes are communicated to data owners.
  • Drive adoption of taxonomy best practices across teams through education, training and guidance.
  • Collaborate closely with ontologists to define core concepts and entities (nodes) that serve as the foundation for the enterprise knowledge graphs.
  • Ensure taxonomy aligns with the broader ontology to support complex reasoning and data integration across systems.
  • Ensure alignment with industry standards (e.g., ACORD) to maintain data consistency across external reporting and internal systems.
  • Standardize tagging models and classification systems to support scalable, modular content across platforms and business units.
  • Evaluate and recommend automated tools (NLP/GenAI) for classification and tag suggestion; manage the feedback loop to continuously refine the taxonomy based on model performance.
  • Implement and manage taxonomy standards using formats like SKOS (Simple Knowledge Organization System) for integration into semantic platforms.
Qualifications
  • Education:

    Bachelor s or master s degree in computer science, Linguistics, Information Science, or a related field with a focus on knowledge representation.
  • 5+ years of experience in taxonomy and controlled vocabularies development, ideally within a complex, highly regulated industry such as Insurance or Financial Services.
  • Strong proficiency in data analysis using tools like Python, SQL, etc.
  • Experience working with graph databases (e.g., Neo4j, Stardog, etc.).
  • Demonstrated experience working directly with data science, machine learning, or software engineering teams.
  • Experience supporting AI/ML, advanced analytics, and real-time data applications.
  • Deep knowledge of semantic standards like SKOS and tools used for taxonomy management.
  • Excellent…
Position Requirements
10+ Years work experience
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