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Ontologist, Product Knowledge Ontology, Product Knowledge Ontology

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Amazon

1mo ago

  • Job
    Full-time
    Entry & Junior Level
  • Data
    Research & Development
  • Munich

AI generated summary

  • You need a relevant degree, 0-2 years’ ontology/taxonomy experience, data retrieval skills, familiarity with Semantic Web tech, strong communication, detail orientation, and proficiency in SQL/SPARQL.
  • You will develop and optimize data models for product knowledge, analyze user behavior, create schemas using generative AI, and collaborate with teams to enhance discoverability and ontology practices.

Requirements

  • 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
  • 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

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

FAQs

What qualifications are required for the Ontologist position?

A degree in Library Science, Information Systems, Linguistics, or equivalent professional experience is required.

Is there an experience requirement for this role?

The position is open to candidates with 0-2 years of relevant experience in developing ontology or taxonomy data models.

What skills are important for this position?

Proven skills in data retrieval and data research techniques, the ability to understand complex processes, and familiarity with Semantic Web technologies (RDF/s, OWL), query languages (SPARQL), and validation/reasoning standards (SHACL, SPIN) are important.

Do I need to be proficient in any specific tools for this role?

Yes, familiarity with open-source or commercial ontology engineering editors such as Protege, TopQuadrant products, or PoolParty is preferred.

What will my main responsibilities be as an Ontologist?

Your main responsibilities will include developing semantically rich data models, ensuring comprehensive product knowledge coverage, researching product information, utilizing data retrieval techniques, and coordinating cross-functional projects.

Is there a focus on collaboration in this role?

Yes, this position involves collaboration with business partners, data science, and engineering teams to create knowledge-based solutions for product discoverability.

What kind of projects will I be working on?

You will be working on projects aimed at creating taxonomy and ontology models to optimize product discovery for Amazon's web and mobile experiences.

How does Amazon support diversity and inclusion in the workplace?

Amazon celebrates diverse cultures and backgrounds within its teams and is committed to fostering a culture of inclusion, offering access to internal affinity groups, and highlighting diversity programs.

Will I receive training and support for my career growth at Amazon?

Yes, Amazon provides continuous support throughout your career, from initial training sessions to ongoing career development opportunities.

Are there any specific technological skills mentioned for this position?

Yes, proficiency in SQL, SPARQL, and familiarity with software engineering life cycles, data science, or machine learning, including graph embeddings, are beneficial for this role.

Retail & Consumer Goods
Industry
10,001+
Employees
1994
Founded Year

Mission & Purpose

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one. Together, Amazonians research and develop new technologies from Amazon Web Services to Alexa on behalf of our customers: shoppers, sellers, content creators, and developers around the world. Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind. You'll also hear us say that at Amazon, it's always "Day 1."​ What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.