Data Scientist - Search Insights (EMEA)

Data Scientist - Search Insights (EMEA)

This job is no longer open
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them. We ask that our team members be physically located in Central European time or Eastern Standard/Daylight time zones for the purposes of our collaboration hours.

The Spotify search team is looking for seasoned data scientist with significant experience in experimentation strategy, online and offline evaluation strategy, and success metrics development to join our team.

We take full responsibility for Spotify search platform, which serves 356 million users in 178 markets. You will join a team where everyone shares a common interest in scalability. Together we try to find new ways to create a great Spotify experience for all our users at all times.

Above all, your work will impact the way the world experiences audio. Our organization strives to make every user session amazing through personalization and discovery.

What You'll Do:

    • Experimentation strategy including AB test design and analysis.
    • Success metrics creation and scalability of Spotify's search services.
    • Work cross functionally with partners in our other European and Americas office locations.
    • Perform advanced analytics including coding (such as Python, R, or Scala) and utilization of analytics and visualization tools (SQL, Tableau, ggplot/matplotlib or equivalent).

Who You Are:

    • 3+ years of professional experience as a data scientist in related tech/consumer field
    • You have a user-focused mentality. You understand the role and importance of qualitative methodologies and you can articulate this, this is a must.
    • Significant experience working with a large datasets ecosystems.
    • Have strong mathematical and statistical understanding of experimentation and non experimentation-based attribution methodologies.
    • You’re a fantastic communicator and shine most at motivating others to carry forward and execute a strategy without needing to be in the room.
    • You bring passion and playfulness to your work and those around you.

Where You'll Be:

    • We are a distributed workforce enabling our band members to find a work mode that is best for them!
    • Where in the world? For this role, it can be within the EMEA region in which we have a work location and is within working hours.
    • Working hours? We operate within the Central European and GMT time zones for collaboration and ask that all be located that time zone.
    • Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
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.

Spotify transformed music listening forever when we launched in 2008. 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 chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service with a community of more than 345 million users.
This job is no longer open
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