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Senior Data Scientist, Artist-First AI Music lab

Role overview

Summary

This role focuses on advancing generative technologies for music within Spotify's Artist-First AI Music lab. You will contribute to building tools that enhance the connection between artists and fans while ensuring fair compensation and participation for creators.

Qualifications

  • Significant hands-on experience in advanced analytics or data science.
  • Proficient in advanced analytics with Python and SQL.
  • Experience developing metrics frameworks for complex products.
  • Experience with machine learning frameworks and validating models.
  • Solid grounding in experimental design and causal inference.

Responsibilities

  • Lead foundational measurement and insights work for generative music experiences.
  • Design and run large-scale analyses and evaluations of generative music systems.
  • Partner with Engineers and AI Researchers to integrate evaluation signals into model development loops.
  • Build practical, scalable metrics and decision systems that define what 'good' looks like for AI music.

Key facts

Hard skills

Other skills

  • Communication
  • Collaboration
  • Problem Solving

About the company

Spotify logo

Spotify

  • Music & Audio
  • XLarge
  • 5,001–10,000
Our mission is to unlock the potential of human creativity—by giving a million creative artists the opportunity to live off their art and billions of fans the opportunity to enjoy and be inspired by it. Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 70m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience. Today, Spotify is the most popular global audio streaming service with 365m users, including 165m subscribers across 178 markets. We are the largest driver of revenue to the music business today.

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Job description

The Music Mission team owns Spotify's end to end proposition for music creators and the experiences they create for fans. The team is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale.

We're looking for a Senior Data Scientist to join the Artist-First AI Music lab. Our team explores and advances generative technologies for music to create new experiences for fans and artists, with a focus on listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles:

Partnerships with record labels, distributors, and music publishers: We'll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later.

Choice in participation: We recognize there's a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music.

Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions.

Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will use our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections.

For more information, see this press release: https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/


What You'll Do
  • Lead foundational measurement and insights work for generative music experiences, developing the frameworks that help Spotify 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 Spotify's unique 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, making sure scientific rigor informs technical direction.
  • Identify the behavioral and market dynamics that shape sustainable consumer demand and creator participation, and translate them into clear strategic recommendations.
  • Build practical, scalable metrics and decision systems that define what "good" looks like for AI music: credibility, user delight, safety, creator alignment, and ecosystem trust.
  • Bring together model, user behavior, and ecosystem signals into clear narratives that shape product strategy, cross-functional alignment, and long-term priorities across Spotify.
  • Create the datasets, dashboards, and long-term measurement systems that give Spotify a lasting, comprehensive understanding of product health and impact.
  • Work closely with Product, Design, Research, Legal, Trust & Safety, Marketing, Policy, and Licensing teams, bringing statistical rigor and principled measurement to help build artist-first systems that scale responsibly.

  • Who You Are
  • You have a track record of using insights to shape strategy for major company initiatives involving many different partners.
  • You have significant hands-on experience in advanced analytics or data science, ideally in a domain involving LLM evaluation, user-generated content, or complex user behavior.
  • You communicate clearly, form well-founded, evidence-backed points of view, and can bring together messy, multimodal signals (quantitative, qualitative, and model telemetry) into clear narratives for senior executives, researchers, engineers, and the music industry.
  • You're proficient in advanced analytics with Python and SQL, have analyzed large datasets, and use AI tools (e.g. Cursor, Copilot) to increase your productivity and impact.
  • You have experience developing metrics frameworks for complex products that help teams measure impact and reason clearly about priorities.
  • You have experience with machine learning frameworks, designing and assessing multimodal or embedding-based models, and validating them against LLM judges or human ground truth, with an understanding of how to evaluate models beyond offline accuracy.
  • You have a solid grounding in experimental design and causal inference, such as A/B tests, quasi-experiments, and power analysis.
  • You thrive when tackling loosely defined problems in ambiguous, zero-to-one spaces.

  • Where You'll Be
  • 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
  • This team operates within the US Eastern timezone for collaboration
  •   The United States base range for this position is $144,714–$206,735 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
    Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.   At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.  

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