Senior Data Scientist, Artist-First AI Music lab

Spotify•Washington, DC

30d•$144,714 - $206,735•Hybrid

About The Position

The Music Mission team owns Spotify’s end-to-end proposition for music creators and the experiences they create for fans. The Artist-First AI Music lab explores and advances generative music technologies to create new experiences for fans and artists, with a focus on listening experiences that center and celebrate artists and creatives. Its products are guided by partnerships with music industry rights holders, choice in participation, fair compensation and new revenue, and strengthening artist-fan connections without replacing human artistry. The Senior Data Scientist will lead foundational measurement and insights for generative music experiences. The role develops frameworks for understanding how creators, listeners, and rights holders engage with generative AI music; evaluates generative music systems; integrates evaluation signals into model-development and product workflows; and translates behavioral and market insights into strategy. The position works across Product, Design, Research, Legal, Trust & Safety, Marketing, Policy, Licensing, Engineering, and AI Research to build scalable metrics, decision systems, datasets, dashboards, and long-term measurement that support responsible, artist-first products. The role offers flexibility in where work is performed, with some in-person meetings, and the team collaborates within the US Eastern timezone.

Requirements

Track record of using insights to shape strategy for major company initiatives involving multiple partners.
Significant hands-on experience in advanced analytics or data science, ideally involving LLM evaluation, user-generated content, or complex user behavior.
Clear communication skills and ability to form evidence-backed points of view and synthesize quantitative, qualitative, and model-telemetry signals into narratives for senior executives, researchers, engineers, and the music industry.
Proficiency in advanced analytics with Python and SQL, experience analyzing large datasets, and use of AI tools such as Cursor or Copilot to increase productivity and impact.
Experience developing metrics frameworks for complex products to measure impact and clarify priorities.
Experience with machine-learning frameworks; designing and assessing multimodal or embedding-based models; validating models against LLM judges or human ground truth; and understanding model evaluation beyond offline accuracy.
Solid grounding in experimental design and causal inference, including A/B tests, quasi-experiments, and power analysis.
Ability to tackle loosely defined problems in ambiguous, zero-to-one environments.

Responsibilities

Lead foundational measurement and insights work for generative music experiences, developing frameworks to understand how creators, listeners, and rights holders engage with generative AI music.
Design and run large-scale analyses and evaluations of generative music systems, from prompt interpretation to model output quality, using behavioral datasets, annotations, and experimentation platforms.
Partner with Engineers and AI Researchers to integrate evaluation signals into model-development loops, debugging workflows, and product iteration.
Identify behavioral and market dynamics that shape sustainable consumer demand and creator participation, and translate them into strategic recommendations.
Build scalable metrics and decision systems to assess AI music credibility, user delight, safety, creator alignment, and ecosystem trust.
Bring together model, user-behavior, and ecosystem signals into narratives that shape product strategy, cross-functional alignment, and long-term priorities.
Create datasets, dashboards, and long-term measurement systems to provide a comprehensive understanding of product health and impact.
Work with Product, Design, Research, Legal, Trust & Safety, Marketing, Policy, and Licensing teams, applying statistical rigor and principled measurement to responsible product development.