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 The Data, Insights, Science and Optimization, Music Product and Tech (DISCO MPT) team is looking for a Data 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 experiences. In 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 Senior Data Scientists to analyze and propose success and guardrail metrics • Encourage the use of experimentation and advanced analytics across the organization 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. Basic Qualifications - Master's degree in computer science, math, engineering, physics, economics or similar fields, or equivalent work experience. - Data Scientist experience - Experience with data querying languages (e.g. SQL, Hadoop/Hive) - Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment Preferred Qualifications - Experience in a ML or data scientist role with a large technology company 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. 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.