Ontologist, Product Knowledge Ontology, Product Knowledge Ontology

* Degree in Library Science, Information Systems, Linguistics or equivalent professional experience
- 0-2 years of relevant experience developing ontology or taxonomy data models
- Proven skills in data retrieval and data research techniques
- Ability to quickly understand complex processes and communicate them in simple language
- Familiarity with Semantic Web technologies (RDF/s, OWL), query languages (SPARQL) and validation/reasoning standards (SHACL, SPIN)
- Familiarity with open-source or commercial ontology engineering editors (e.g. Protege, TopQuadrant products, PoolParty)
- Detail-oriented problem solver who is able to work in fast-changing environment and manage ambiguity
- Proven track record of strong communication and interpersonal skills
- Proficient English language skills
The vision of the Product Knowledge Ontology Team is to provide a standardized, semantically rich, easily discoverable, extensible, and universally applicable body of product knowledge that can be consistently utilized across customer shopping experiences, selling partner listing experiences and internal enrichment of product data. We aim to make product knowledge compelling, easy to use, and feature rich. Our work to build comprehensive product knowledge allows us to semantically understand a customer’s intent - whether that is a shopping mission or a seller offering products. We strive to make these experiences more intuitive for all customers. As an Ontologist, you work on a global team of knowledge builders to deliver world-class, intuitive, and comprehensive taxonomy and ontology models to optimize product discovery for Amazon web and mobile experiences. You collaborate with business partners, data science and engineering teams to deliver knowledge-based solutions to enable product discoverability for customers. In this role, you will directly impact the customer experience as well as the company’s product knowledge foundation. Key job responsibilities
- Develop logical, semantically rich, and extensible data models for Amazon's extensive product catalog
- Ensure our ontologies provide comprehensive product knowledge entities coverage that are available for machine ingestion and inference
- Research worldwide understanding of Amazon products to develop scalable data models that solve customer problems and enhance product discoverability
- Leverage existing data retrieval techniques by utilizing our extensive product catalog and query languages
- Create new schema using Generative Artificial Intelligence (generative AI) models
- Analyze website metrics and customer’s browsing and searching activities to make data-driven decisions on optimizing our knowledge graph data models globally
- Drive awareness of ontology modeling and technology best practices and principles within our organization and across Amazon
- Coordinate cross-functional projects with technical and non-technical teams About the team Our team has a global presence: we celebrate diverse cultures and backgrounds within our team and our customer base. We are committed to furthering our culture of inclusion, offering continuous access to internal affinity groups as well as highlighting diversity programs. We care about your career growth, from your initial company introduction and training sessions, to continuous support throughout your entire career at Amazon. We recognize each team member as an individual, and we will build on your skills to help you grow. We have a broad mix of experience levels and tenures, and we are building an environment that celebrates knowledge sharing.
- Master’s degree in Library Science, Information Systems, Linguistics or other relevant fields
- Experience building ontologies in the e-commerce and semantic search spaces
- Experience working with schema-level constructs (e.g. higher-order classes, punning, property inheritance)
- Proficiency in SQL, SPARQL
- Familiarity with software engineering life cycle
- Exposure to data science and/or machine learning, including graph embeddings

m/w/d