Spotify

Data Scientist - Music Mission

New York, NY

Sponsorship not specified$117k-$167kDetected 29 days ago

PythonAlgorithmsSQLBigQueryMachine LearningdbtData ScienceStatisticsA/B Testing

About the role

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.
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.
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.

Discovery Mode is a tool for artists and music marketers designed to help find new listeners when it matters most.
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.

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.

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

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.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone.
We're looking for a Data Scientist to join Discovery Mode within the Music Mission.
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.

This listing is sourced directly from Spotify's careers page and normalized into a canonical job model.