Staff Data Scientist

Who you are

• You have deep experience as a product data scientist and have operated at Staff level or equivalent
• You have a strong foundation in statistics and experience designing evaluation and measurement approaches, including annotation-based methods and settings where controlled experiments are not feasible
• You have experience in building metrics and reporting systems that support product or policy decision-making
• You have built self-serve analytical tools or data agents that enable others to answer questions effectively
• You are proficient in SQL and experienced with Python, DBT, or similar tools for building and maintaining reliable analytical datasets
• You leverage state of the art LLM models to do your analysis while ensuring quality and accuracy in the output
• You communicate clearly across functions, influence decisions with senior stakeholders, and help raise analytical standards through mentorship and methodological leadership
• You have experience working on content classification, taxonomy, safety, policy, or adjacent domains where data quality and judgment are important to product decisions

What the job involves

• Content Platform is responsible for the full content lifecycle at Spotify — from ingestion through to delivery — across music, podcasts, and audiobooks. We ensure content is structured, evaluated, and delivered reliably at global scale, powered by deep content understanding
• We bring valuable content to users while ensuring it remains trusted and high-quality over time. The Product Insights team works across the full content lifecycle to improve decision-making, improve our catalog understanding and ensure one of the world’s largest content catalogs is safe and engaging
• We’re looking for a Staff Data Scientist to join the team and tackle complex, high-impact problems by combining strategic thinking with hands-on, tactical execution
• Lead analyses across user behavior and content data to shape product and strategy decisions
• Shape how we evaluate and improve content classification and taxonomy, with a particular focus on safety, combining analytical depth with a broader view of product and business needs
• Design evaluation frameworks, including sampling strategies, setting baselines, metrics, and annotation-based approaches, and guide how these methods are applied across the team
• Build scalable analytical foundations, including metrics, dashboards, and the data and context needed to enable effective self-serve analysis and agents
• Partner with Product, Engineering, and Operations leadership to shape priorities and how data informs product strategy
• Raise the analytical bar across Product Insights through methodological leadership, mentorship, and by identifying opportunities to improve how we work with data across domains

Benefits

• Extensive learning opportunities, through our dedicated team, GreenHouse
• Flexible share incentives letting you choose how you share in our success
• Global parental leave, six months off - fully paid - for all new parents
• All The Feels, our employee assistance program and self-care hub
• Flexible public holidays, swap days off according to your values and beliefs