We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
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.
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.
As a Lead Decision Scientist, you will partner with product and engineering teams to drive data-informed decisions, establish causality, and shape the AI-native analytics environment.
Lead a team of machine learning engineers and data scientists to develop and deploy innovative styling algorithms that enhance client personalization experiences.
As a lead product data scientist on the team, you will play a critical role in shaping our growth strategy, up-leveling our experimentation culture, and scaling our business.
As a Lead Data Scientist for LATAM, you'll drive data science strategy and hands-on model development across Mexico and Brazil, mentoring a team while establishing foundational practices.
As an Analytical Engineering Manager, you will lead a team responsible for data foundations, ensuring stakeholder trust in data quality and enabling self-service analytics.
