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Job description
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.
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
We offer you the flexibility to work where you work best! For this role, you can be within the EST timezone region as long as we have a work location.
This team operates within the Eastern Standard time zone for collaboration.
The United States base range for this position is $116,994 - $167,135 USD, plus equity.
health insurance
six-month paid parental leave
401(k) retirement plan
monthly meal allowance
23 paid days off
paid flexible holidays
paid sick leave
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here:
Today, we are the world’s most popular audio streaming subscription service.
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.