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Metro-based mid-level role with common experience band and known brand yields moderate competition.
Specialized video taxonomy and annotation skills transfer to AI/media roles but are less transferable to unrelated industries.
Explicit 2–5 years plus taxonomy and tooling experience creates moderately strict screening.
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Manage and evolve foundational taxonomy and categorization systems for video metadata to support AI models.
Execute detailed video data labeling and organize large raw datasets ensuring quality and consistency.
Scale training data efforts using external annotation platforms and crowdsourced services like Labelbox and AWS Mechanical Turk.
2–5 years of experience related to taxonomy, library science, archival organization, or media categorization.
Familiarity with data labeling tools (e.g., Labelbox) and crowdsourced annotation services (e.g., Mechanical Turk).
Hybrid work model requiring proximity to Nielsen’s office in the same city for partial on-site work.
Work Experience Required: 2–5 years as described above.
Strong operational focus on maintaining and scaling high-quality, structured video data for AI training.
Experience working with global teams in a flexible, hybrid work environment.
Detail-oriented with a proven ability to organize complex data assets and improve data accuracy and classification.