About TRANSFORM

Transform, Inc. delivers the first machine-learning and AI platform for video that answers the fundamental questions of why audiences connect, react and engage. Our innovative software analyzes the creative essence of video, allowing companies to see direct connections between their content and viewer behaviors. Transform’s technology can be tailored for any video content -- TV shows, trailers, local newscasts, consumer and retail ads -- providing actionable insights that help increase viewing, subscriptions and purchases.

PRODUCT TEAM

About the BEHAVIORAL SCIENTIST ROLE

The Behavioral Scientist, above all, is an expert quantifier of human behavior. This means continuous ideation, refinement and tuning of both semantic groups of tagged elements derived from film, TV, music videos, ads trailers, and a variety of other media types, as well as knowledge graphs for human response to video. You know how to frame and reframe information into meaningful clusters, buckets, tribes, networks or maps, and communicate the most reliable approach to a team of data engineers. Behavioral Scientists are crucial to Transform. They are responsible for ensuring that video content analysis always hits its mark. They are open to input, but ultimately know how to produce concrete frameworks for interpreting the elements inside video that bring us joy, sadness, fear, anger, excitement - and compel us to tell everyone about it. Reporting to the Head of Product, you will work with Transform’s engineering teams and media subject matter experts to improve Transform’s ability to revolutionize the way video content creators engage their audiences. You will produce conceptual documentation, research comparable knowledge graphs and classification approaches, improve terminology for tagged elements, and enable the engineering team to leverage your ideas. You might have experience as a library scientist, information architect, applied psychologist, behavioral economist, or you may be familiar with Natural Language Processing, linguistics, film production or search classification.

Responsibilities

  • Own the development of concrete knowledge graphs for semantic groups of content tags

  • Aid the engineering team in the deployment of semantic taxonomies and knowledge graphs

  • Assist with specific projects where new content analysis is required

  • Research and create innovative approaches to classification of video content

  • Use evidence-based approaches from customer data to optimize and improve classifications

  • Collaborate with Engineering, particularly data science, machine learning and natural language processing specialists, as well as technical writers, to produce foundational documentation

  • Make a strong case for your approach to classifications, while taking careful heed of subject matter expert input

  • Develop A/B tests for classifications and user engagement within customer OTT systems

About You

Minimum Qualifications:

  • BS in Psychology, Behavioral Economics, Information Science, Information Architecture or Library Science

  • 2 years of relevant experience, such as managing large online catalogs of products, content, information or archives

  • Examples of prior creation, standardization and deployment of metadata frameworks

  • Proven work experience in a self-directed environment with demonstrated ability to contribute to a team

  • Strong data analysis and interpretation skills

  • Proficient english writing and editing skills

  • Ability to meet deadlines

Preferred Qualifications:

  • Direct experience with digital asset management in media and entertainment industry settings

  • Film and television superfan

  • 4+ years of relevant work experience, such as managing large online catalogs of products, content, information or archives

  • Ability to manage multiple competing priorities in a fast-paced, constantly changing environment

  • MS in Psychology, Behavioral Economics, Information Science, Information Architecture or Library Science


  Email our team at careers@transform.digital