Creator Marketplace is the home for Spotify’s music industry products, such as Spotify for Artists, Spotify Label Analytics and Spotify Publisher Analytics.
The Creator Product Insights Team is a growing insights community of 20+ Data Scientists and User Researchers who blend their skills to help us craft the future of the Creator Marketplace by defining the next generation of music industry products. We transform data into insights that impact our strategy and products.
Our team is looking for a data scientist to join the band and help us build the data ecosystem that powers our analysis of consumption on the platform and informs our understanding of the larger industry.
You will work with data engineers, data scientists, user researchers and product managers to architect systems and pipelines needed to tackle questions at the petabyte scale of artist-listener relationships such as: How do we help artists stand out? How do we help them grow and reach new audiences? How do we help them connect with their fans?
Your work will influence the future of Spotify and the way the world experiences music.
What You’ll Do
- Engineer lasting solutions for surfacing critical data that helps us understand our platform.
- Build and be responsible for the analytics layer of our team’s data environment, making data standardized, easily accessible and high quality.
- Collaborate with, and mentor, data scientists in building scalable analyses and datasets.
- Contribute to the development of the Product Insights function and the wider analytics community at Spotify.
- Work from our offices in New York.
Who You Are
- You are a communicative person who values building strong relationships with colleagues and partners, enjoys mentoring and teaching others and you have the ability to explain complex topics in simple terms
- You have at least 4 years of experience in a similar data science, data engineering, or data analysis role
- Degree in computer science, engineering, physics, statistics, economics, mathematics, or similar quantitative discipline
- Significant experience in designing analytical data layers and in conducting ETL with large and complex data sets.
- Experience with feature engineering for machine learning models.
- Knowledgeable in data modeling, data access and data storage techniques.
- High level of ability in SQL, Scala and Python
We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come to be a part of changing the way the world listens to music.