Data Scientist, Music Search Platform - Science & Modeling
Amazon - San Francisco, California, United States, 94199![Amazon](/api/image?src=https%3A%2F%2Fgeneral-board-default.s3.us-east-2.amazonaws.com%2Fpublic%2Fimages%2Fdesk-360x180.webp&w=640&q=75&f=webp)
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Read all the information about this opportunity carefully, then use the application button below to send your CV and application.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. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale.The Amazon Music Search Platform - Science & Modeling team is seeking an experienced Data Scientist who will join a team of experts in the field of machine learning. You'll work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.Key job responsibilities You'll work in a collaborative environment where you can pursue ambitious, long-term research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research.BASIC QUALIFICATIONS
1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experienceBachelor's degreePREFERRED QUALIFICATIONS
Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or RExperience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.Posted:
May 9, 2024
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