Data Scientist - Music Mission

Spotify•New York, NY

6h•$110,018 - $157,169•Remote

About The Position

We are seeking a Data Scientist to join Spotify’s Artist-First AI Music Lab. Our team pioneers state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new products that center and celebrate artists and creatives—putting artists and songwriters first through principles of choice, transparency, fair compensation, and deepened artist–fan connection. As a Data Scientist on this team, you’ll help bridge cutting edge AI research with outstanding product experiences. Your work will ensure that every feature we launch is grounded in data-driven insight and meaningfully strengthens the connection between more than 700 million listeners and the creators they love. For more information, see this press release: https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/

Requirements

You have a degree in Computer Science, Statistics, Economics, Operations Research, quantitative social science, or a related field (or equivalent experience)
You bring 4+ years of experience as a Data Scientist influencing product decisions through data
You’re highly proficient in SQL and Python and comfortable working with large-scale datasets
You use AI-powered tools (e.g., Cursor, Copilot) to accelerate analysis and workflows
You have strong product intuition and a results-focused perspective— you seek the “why” behind the data
You have experience with A/B testing, causal inference and advanced statistical methods, and exercise strong judgment in methodological choices
You understand machine learning systems and can evaluate models beyond offline metrics, applying human judgment to quality and impact
You thrive in ambiguous, zero-to-one environments and enjoy defining metrics & opportunities for entirely new product categories
You’re motivated by creating real value for music fans and music creators

Responsibilities

Own analytical projects end-to-end, from hypothesis generation and data exploration to recommendations for product leadership
Develop and own success metrics for generative music features and systems
Design and analyze A/B tests and causal studies to evaluate product and model impact
Perform exploratory analyses to uncover opportunities that improve experiences for listeners and artists
Build scalable dashboards to monitor feature health and ecosystem impact
Design and run evaluations for generative music systems, assessing risks and opportunities across prompts, outputs, and quality
Collaborate with Product, Design, Research, Marketing, and Engineering to translate insights into product requirements
Partner closely with Engineers and AI Researchers to integrate evaluation signals into model development workflows
Communicate complex findings through clear, actionable narratives that inform product strategy and roadmap decisions