Description

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music.
Embark on an exhilarating journey with the DISCO team at Amazon Music!

As a technologist, you’ll have end-to-end ownership of the science product, design, and technology required to deliver state-of-the-art experiences for our internal customers. Join us in championing a culture of inclusivity and a data-driven mindset, where every team member at Amazon Music is empowered to make informed decisions and measure their impact. Be the driving force behind delivering top-notch, accessible data and democratizing data access through user-friendly self-service tools. Join us on this exciting quest to redefine how we approach insights and decision-making for all!


Key job responsibilities
As a Data Scientist on this team you will:
- Lead Data Science solutions from beginning to end.
- Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate leading generative AI solutions to address real-world challenges
- Deliver with independence on challenging large-scale problems with complexity and ambiguity.
- Write code (Python, Scala, SQL, etc.) to obtain, manipulate, and analyze data.
- Build Machine Learning and statistical models to solve specific business problems.
- Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
- Analyze historical data to identify trends and support optimal decision making.
- Apply statistical and machine learning knowledge to specific business problems and data.
- Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.
- Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.

- Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.