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.
Imagine shaping how millions of customers discover and engage with digital music and audio, leveraging the resources of a Fortune-500 company within the atmosphere of a start-up. Love collaborating with a wide range of internal and external partners to drive successful partnerships? If so, come and build the future of music and audio with us.
Transform how people enjoy music, audiobooks & podcasts with personalized recommendations as our Applied Scientist in Berlin. Support the design, development & deployment of data-driven models that recommend the right content at the right time based on customer context & behaviour. Leverage audio data, metadata & listening patterns to create innovative features that personalize the Amazon Music experience. Collaborate with engineers and business teams to ensure coherent personalization across Amazon Music, from conception to production. You will make listening magical again through the power of personalization!
Please note this is a fixed term contract until July 2026
Key job responsibilities
- Create Innovative ML Solutions for Customized Musical Joy. Through A/B testing and online experiments done hand-in-hand with engineering teams, you'll implement and validate your ideas and solutions.
- Chart the Course to Musical Discovery. Seek new directions to guide Amazon Music's quest to match each customer with their perfect playlists.
A day in the life
Lead innovation to shape Amazon Music experiences. Collaborate with talented engineers and scientists to guide research and build scalable models across our audio portfolio - music, podcasts, live streaming, and more. Drive experiments and rapid prototyping, leveraging Amazon's data at scale. Innovate to delight customers worldwide through personalization.
About the team
Bring music to life through machine learning! Our Berlin teams breathe passion into Amazon Music, optimizing each recommendation for our customers' unique tastes. Scale your work across music apps, web player and Alexa devices, fine-tuning the algorithms behind our recommendation and personalization features. Collaborate with global teams to create the future of musical engagement, one stream at a time. Help us surprise and delight Amazon Music fans with an ever-better listening experience. Join our mission to personalize music through machine learning!
- Experience programming or scripting language like Python, Java, C or C++
- Experience in building models for business application
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience working effectively with science, data processing, and software engineering teams
- Experience in professional software development
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 (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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