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  • Munich, Bayern, Deutschland Amazon Development Center Germany GmbH Vollzeit

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  • Munich, Bayern, Deutschland Amazon Development Center Germany GmbH Vollzeit

    Job Title: Senior Ontologist, Product KnowledgeAbout the Role:We are seeking a highly skilled Senior Ontologist to join our Product Knowledge team at Amazon Development Center Germany GmbH. As a key member of our team, you will play a critical role in developing and maintaining our product knowledge foundation, enabling seamless customer experiences across...


  • Munich, Bayern, Deutschland Amazon Development Center Germany GmbH Vollzeit

    About the RoleThe Product Knowledge Ontology Team at Amazon Development Center Germany GmbH is seeking an experienced Ontologist to join our global team of knowledge builders. As an Ontologist, you will play a critical role in delivering world-class, intuitive, and comprehensive taxonomy and ontology models to optimize product discovery for Amazon's web and...

Senior Knowledge Architect, Product Ontology

vor 3 Monaten


Munich, Bayern, Deutschland Amazon Development Center Germany GmbH Vollzeit

Job Location:
Munich (this is not a remote opportunity).


The Ontology Product Knowledge Team envisions delivering a standardized, semantically rich, easily discoverable, extensible, and universally applicable body of product knowledge that can be consistently utilized across various customer shopping experiences, selling partner listing experiences, and internal product data enrichment.

Our goal is to create product knowledge that is engaging, user-friendly, and feature-rich.

By building comprehensive product knowledge, we aim to semantically comprehend customer intent, whether it pertains to a shopping mission or a seller offering products.

We strive to enhance these experiences, making them more intuitive for all customers.


As an Ontologist, you will collaborate with a global team of knowledge builders to deliver world-class, intuitive, and comprehensive taxonomy and ontology models that optimize product discovery for Amazon's web and mobile platforms.

You will work alongside business partners and engineering teams to provide knowledge-based solutions that enhance product discoverability for customers. In this role, your contributions will significantly impact both the customer experience and the foundational product knowledge of the company.

Key Responsibilities:

  • Develop logical, semantically rich, and extensible data models for Amazon's extensive product catalog.
  • Ensure our ontologies cover comprehensive domains that are accessible for both human and machine ingestion and inference.
  • Create new schemas utilizing Generative Artificial Intelligence (generative AI) models.
  • Analyze website metrics and product discovery behaviors to make data-driven decisions for optimizing our global knowledge graph data models.
  • Expand and refine data retrieval techniques to leverage our extensive knowledge graph.
  • Contribute to team goal setting and future vision development.
  • Drive and coordinate cross-functional projects with a diverse range of merchandisers, engineers, designers, and other groups, which may include architecting new data solutions.
  • Develop operational excellence programs, data quality initiatives, and process simplifications for the team.
  • Advocate for ontology and semantic technologies within and across teams at Amazon.
  • Develop and refine data governance and processes utilized by global Ontologists.
  • Mentor and influence peers.

Inclusive Team Culture:

Our team has a global presence, celebrating diverse cultures and backgrounds within our team and customer base.

We are dedicated to fostering a culture of inclusion, providing continuous access to internal affinity groups and highlighting diversity programs.


Work/Life Harmony:
Our team believes that achieving a balance between work and personal life is essential. Our work is influenced by everyday life, not separate from it.

We offer flexible working hours and will collaborate with you to facilitate your balance between work and personal commitments.


Career Growth:

Our team is invested in your career development, from your initial company introduction and training sessions to ongoing support throughout your career at Amazon.

We recognize each team member as an individual and will build on your skills to foster your growth.

We have a diverse mix of experience levels and tenures, creating an environment that celebrates knowledge sharing.


Benefits:

  • You will have the opportunity to support customer experiences used by millions daily and work with data at an unparalleled scale.
  • We have offices worldwide, providing opportunities for global placements.
  • You'll receive on-the-job training and group development opportunities.
BASIC QUALIFICATIONS

  • Degree in Library Science, Information Systems, Linguistics, or equivalent professional experience.
  • 5+ years of relevant experience in ontology and/or taxonomy roles.
  • Proven skills in data retrieval and research techniques.
  • Ability to quickly grasp complex processes and communicate them clearly.
  • Experience in creating and conveying technical requirements to engineering teams.
  • Ability to communicate effectively with senior leadership (Director and VP levels).
  • Experience with generative AI (e.g., creating prompts).
  • Knowledge of Semantic Web technologies (RDF/s, OWL), query languages (SPARQL), and validation/reasoning standards (SHACL, SPIN).
  • Familiarity with open-source and commercial ontology engineering editors (e.g., Protege, TopQuadrant products, PoolParty).
  • Detail-oriented problem solver capable of thriving in a fast-paced environment and managing ambiguity.
  • Proven track record of strong communication and interpersonal skills.
  • Proficient English language skills.
PREFERRED QUALIFICATIONS

  • Master's degree in Library Science, Information Systems, Linguistics, or other relevant fields.
  • Experience in building ontologies within the e-commerce and semantic search domains.
  • Experience with schema-level constructs (e.g., higher-level classes, punning, property inheritance).
  • Proficiency in SQL, SPARQL.
  • Familiarity with the software engineering life cycle.
  • Familiarity with ontology manipulation programming libraries.
  • Exposure to data science and/or machine learning, including graph embedding.