Data Scientist, Content Intelligence

New York, NY

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We grow and develop and make wonderful things happen together every day. It doesn't matter who you are, where you come from, what you look like, or what music you love. Join the band!

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Have you ever had a debate at a party about who originally wrote a song versus who covered it? Tried to find a sample you loved more than the song you heard it in?  Wondered who was actually in the recording booth for your favorite song (on both sides of the glass)? Wonder what Britney Spears, Nsync, Pink, Katy Perry, Taylor Swift, and The Weeknd all have in common? (The same songwriter wrote Billboard number-one singles for all of them). Who gets paid every time we sing “Happy Birthday”?
Music attribution at scale is one of the great unsolved technical problems of the music industry, and we’re building cutting-edge technology to solve it. Our goal is to solve this problem for the more than 60 million music tracks playable on Spotify, building a knowledge graph through cutting-edge machine learning models, deep subject matter expertise, and close integration with human-in-the-loop processes across Spotify and the industry. Content Platform’s catalog data powers Spotify experiences from Artist pages in the app, search and recommendations, human playlist curation, Spotify for Artists, and our music industry-facing strategy. 
Our teams are composed of product, machine learning, data and backend engineers, and subject matter experts who average 11 years behind the scenes in the music industry. 
We are looking for a Data Scientist to conduct analysis of our music catalogs. You and your team’s impact will range from building our foundational understanding of what it means to build an enriched, complete audio catalog, to understanding how and when the catalog is consumed by 100+ other teams within Spotify, to identifying the causal impact of improving our catalog’s quality on key business metrics. You will collaborate closely with cross-functional colleagues and use these insights to drive product and business strategies that impact the roadmaps of product teams.
A successful candidate should love product insights and be deeply curious. You should have strong experimentation, metric & data creation, and data visualization skills as well as possess excellent communication skills to interface between technical and product teams!

What You'll Do

  • Contribute to the development of the Product Insights function and the wider analytics community at Spotify.
  • Work closely with data scientists, user researchers, product managers, engineers, and others across the company who are passionate about our content catalog.
  • Define the metrics we use to measure the success and health of products and track them through dashboards.
  • Design, implement, and maintain ETL pipelines in SQL and Google BigQuery.
  • Create insights from large sets of data that will help drive product, design decisions, and business performance.
  • Communicate insights and recommendations to stakeholders across Spotify
  • Be an advocate for data-informed decision-making, making recommendations about the product performance and product experience available to the Marketplace organization.
  • Create insights based on a huge amount of data using cutting-edge data science tools and methodologies.
  • Work with distributed teams across multiple offices and time zones.

Who You Are

  • You have 5+ years of experience building data science solutions.
  • Degree in data science, computer science, statistics, economics, mathematics, or a similar quantitative field. Ph.D. welcome.
  • You are experienced in programming in at least one language (Python, R, Matlab, ...) and fluent in SQL. BigQuery experience is a plus. 
  • Experience with product analytics, including crafting success metrics, running power analyses, determining statistical significance, and presenting findings with clear product recommendations or implications.
  • Experience visualizing data and/or building dashboards. 
  • Strong communication skills and value building strong relationships with colleagues and partners as well as the ability to explain sophisticated topics in straightforward terms.
  • You’re a compelling storyteller who can communicate in succinct and inspiring ways to audiences with varied data science experience to influence real-world product or feature decisions.
  • Modeling and statistical knowledge, such as forecasting, AB-testing, or statistical modeling and causal inference is a plus.

Where You'll Be

  • We are a distributed workforce enabling our band members to find a work mode best for them!
  • Where in the world? For this role, it can be within the Americas region in which we have a work location.
  • 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.
  • Working hours? We operate within the Eastern Standard time zone for collaboration.
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 381 million users.
This position is not eligible to be performed in Colorado.
Job perks/benefits: Team events
Job region(s): North America
Job stats:  5  1  0
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