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Spotify

Posted 5 months ago

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Data Scientist - Content Understanding

LondonHybridFull-time

AI Summary

Data Scientist II focused on analyzing user behavior, metadata, and machine learning systems to improve content classification, evaluation, and understanding across Spotify.

About this role

Spotify’s consumer product is powered by an enormous and ever-growing catalog of music, podcasts, and audiobooks. The Content Platform team is responsible for making sure that content is ingested, structured, evaluated, and delivered reliably at global scale.
Our work ensures that creators’ content reaches fans quickly and accurately and that Spotify’s catalog is organized in a way that supports discovery, personalization, and a seamless listening experience. We partner closely with engineering, product, operations, labels, distributors, and research teams to keep our content ecosystem robust and scalable.
As a Data Scientist II, you’ll work at the intersection of user behavior, metadata, and machine learning systems to improve how content is classified, evaluated, and understood across Spotify.

What You'll Do

  • Analyze user behavior, content trends, and catalog data to generate insights that shape product decisions.
  • Analyze and refine content classification and taxonomy systems to improve how content is grouped.
  • Develop annotation-based evaluation frameworks, including sampling design and baseline definition, and assess the performance of LLMs used in annotation workflows.
  • Develop and maintain metrics, dashboards, and text-to-SQL environments that support decision-making.
  • Improve dataset quality and data transformations using SQL and DBT to ensure reliable reporting across content and behavioral domains.

    • Who You Are

  • You are experienced in analyzing complex datasets that combine user behavior with content and metadata signals.
  • You have developed metrics and reporting systems that support product or policy decision-making.
  • You have a strong foundation in statistics and experience designing evaluation approaches in environments where controlled experiments are not feasible.
  • You have built annotation-based measurement frameworks, including sampling strategies and baseline definitions.
  • You have designed or applied methods to measure the quality of LLM-generated annotations.
  • You are proficient in SQL and have experience using DBT, Python, or R to build and maintain reliable analytical datasets.
  • You communicate clearly and collaborate effectively with cross-functional teams.

    • Where You'll Be

  • This role is based in Stockholm or London.
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

    • Skills

    Annotation-based MeasurementBaseline DefinitionsDataset QualityData TransformationsDbtExperimentation Non-controlledLLM EvaluationMetrics And DashboardsPythonRSampling StrategiesSQLStatisticsText-to-SQL

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