Applied Scientist, Amazon Music DISCO, Music DISCO

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 Data Insights Science and Optimization Music Product and Tech (DISCO MPT) team is looking for a Applied Scientist to join a team of scientists and engineers who analyze big data provide analytics and insights and build models and algorithms to power Music product this role you will set the science vision and direction for the team and collaborate with internal stakeholders across product science and finance to scale and advance our science offerings. You will lead large scale science solutions prioritize across multiple stakeholders and projects and be part of a fast-paced dynamic and fun environment.

Key job responsibilities
Lead the research and development of models and science products powering personalized recommendations
Partner with product leaders at Amazon Music to develop science-driven business strategies
Partner with science marketing and product teams across Amazon Entertainment and subscription businesses
Educate internal teams on analytics insights and measurement
Develop models to determine drivers of key performance metrics and automate the process of deep diving into variances
Collaborate with product and engineering teams to evaluate the impact of new features or algorithms (e.g. the Playlist Song Recommendation experiments)
Analyze the results of experiments and provide recommendations to optimize solutions
Partner with Data Engineers to develop new product based on GenAI technology
Write high quality production code

About the team
The DISCO team focuses on accelerating Amazon Music customer growth by empowering product teams to make sound customer-centric decisions through data and insights. We build data pipelines self-service analytics insights and predictive models enabling acquisition engagement and retention at scale with personalized customer touchpoints.

- PhD or a Masters degree and experience in CS CE ML or related field
- Experience in building models for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing

- Experience in solving business problems through machine learning data mining and statistical algorithms
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( to know more about how we collect use and transfer the personal data of our candidates.

m/w/d

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.