Data Scientist - Music Mission

The Music Mission enables music creators to grow, engage, and monetize their fan bases on Spotify. Central to the Music Mission's vision is the development of promotional tools for artists and label teams, powered by Spotify's deep knowledge of listener behavior. Products like Discovery Mode, Marquee, Showcase, Music Videos, and Clips help artists and their teams grow their audiences, connect with fans, and achieve their goals on Spotify.

We're looking for a Data Scientist to join Discovery Mode within the Music Mission. Discovery Mode is a tool for artists and music marketers designed to help find new listeners when it matters most. With Discovery Mode, artists and labels identify songs that are a priority, and our systems use that signal to inform the algorithms that power personalized recommendations. This role sits within the ML squad that builds and operates the models behind Discovery Mode's measurement system, and you'll serve as the squad's analytical lead.

In this role, you'll partner closely with product managers and ML engineers to evaluate and improve the models that power Discovery Mode. You'll tackle complex analytical problems by designing experiments, developing evaluation frameworks, and building the analytical foundations that help keep our models accurate, reliable, and impactful for artists. As part of the Product Insights team within Music Mission, you'll help shape the measurement systems behind one of Spotify's most important promotion products.

The United States base range for this position is $116,994 - $167,135 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.

What You'll Do

Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of the models that power measurement and campaign optimization

Partner with ML engineers to develop evaluation frameworks and identify opportunities to improve model performance, reliability, and customer impact

Design and execute rigorous experiments to evaluate model quality, measure outcomes, and guide model development

Conduct deep-dive analyses to assess model performance and translate findings into clear, actionable recommendations for product and business stakeholders

Build, maintain, and evolve dashboards that track model health, customer metrics, and program performance

Collaborate with product managers, engineers, and cross-functional partners to align analytical priorities with squad goals and customer needs

Contribute to the broader Product Insights community by sharing best practices and helping raise the bar for analytics across Discovery Mode

Who You Are

You have 4+ years of experience in a data science role and a degree in data science, statistics, economics, mathematics, or a related quantitative field

You have experience measuring customer outcomes, defining KPIs, and connecting analytical insights to product decisions

You know how to design and implement A/B tests, understand when experimentation is the right tool, and interpret results with appropriate rigor

You have experience evaluating machine learning model performance and partnering with ML engineers to improve model and customer outcomes

You are comfortable working in a highly technical environment and collaborating closely with engineering partners

You communicate complex statistical concepts clearly to both technical and non-technical audiences

You have strong data science fundamentals, including Python, SQL, BigQuery, dbt, data storytelling, and experience working within cross-functional product teams

You have experience in areas such as advertising measurement, recommendation systems, experimentation, or causal inference at scale

Where You'll Be