Job summary

With more than 400 million searchable data items — including 10 million movie, TV and entertainment titles, 11 million cast and crew members and 11 million images — IMDb is the world’s most popular and authoritative source for information on movies, TV shows and celebrities, and has a combined web and mobile audience of more than 200 million monthly visitors. The IMDb database is continually growing, thanks to a vast contributor community of entertainment professionals and companies, IMDb staff, individual contributors and other trusted sources. IMDb content is integrated into strategically important parts of Amazon and AWS businesses, including Amazon Fire TV, Alexa, and X-Ray on Prime Video. IMDb licenses information from its vast and authoritative database to third-party businesses, including film studios, television networks, streaming services and cable companies, as well as airlines, electronics manufacturers, non-profit organizations and software developers. Learn more at developer.imdb.com. 

Other IMDb products and services include: the IMDb website for desktop and mobile devices; apps for iOS and Android; a free streaming channel, IMDb TV; and IMDb original video series and podcasts. For entertainment industry professionals, IMDb provides IMDbPro and Box Office Mojo. IMDb is an Amazon company. For more information, visit imdb.com/press and follow @IMDb.

IMDb is a group of entertainment enthusiasts – and we are passionate about ensuring all our customers around the globe have access to all the content they need, when they need it. IMDb sits at the intersection of the entertainment, media, and technology markets inside the world’s most innovative and consumer-centric company – Amazon.com. IMDb employees enjoy the benefits of working for Amazon with the autonomy of working on a smaller, nimble team.

As an Ontologist, you work as part of a global team to deliver world-class, intuitive, and comprehensive taxonomy and ontology models to optimize product delivery for IMDb web and mobile experiences. You collaborate with business partners and engineering teams to deliver knowledge-based solutions to enable discovery and engagement with IMDb content. In this role you will directly impact the customer experience as well as the company's product knowledge foundation across all customer cohorts.


Specific responsibilities include the following:

Develop logical, semantically rich, and extensible data models for IMDb's expansive entertainment catalog.

Ensure our ontologies provide comprehensive sub-domain coverage that are available for machine ingestion and inference

Research worldwide understanding of entertainment content to develop scalable data models that solve customer problems and enhance entity discovery

Contribute to the development of new tools, features and processes for the Ontology team

Support the content expansion team focused on driving the overall IMDb Content product and business strategy and execution.

BASIC QUALIFICATIONS

Experience working in ontology and/or taxonomy roles
Proven skills in data retrieval and data research techniques
Ability to quickly understand complex processes and communicate them in simple language
Ability to communicate knowledge-based requirements and needs to engineering and retail teams
Familiarity with Semantic Web technologies (RDF/s, OWL), query languages (SPARQL) and validation/reasoning standards (SHACL, SPIN)
Detail-oriented problem-solving, ability to work in fast-changing environment and manage 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 building ontologies in the entertainment 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
Familiarity with ontology manipulation programming libraries
Exposure to data science and/or machine learning, including graph embeddings


Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.