Data Scientist, Amazon Music

Amazon.com Services, Inc.
 Seattle, WA

Desciption

Job summary

Amazon Music

Amazon Music reimagines music listening by enabling customers to unlock millions of songs and thousands of curated playlists and stations with their voice. Amazon Music provides unlimited access to new releases and classic hits across iOS and Android mobile devices, PC, Mac, Echo, and Alexa-enabled devices including Fire TV and more. With Amazon Music, Prime members have access to ad-free listening of 2 million songs at no additional cost to their membership. Listeners can also enjoy the premium subscription service, Amazon Music Unlimited, which provides access to more than 75 million songs and the latest new releases. Amazon Music Unlimited customers also now have access to the highest-quality listening experience available, with more than 75 million songs available in High Definition (HD), more than 7 million songs in Ultra HD, and a growing catalog of spatial audio. Customers also have free access to an ad-supported selection of top playlists and stations on Amazon Music. All Amazon Music tiers now offer a wide selection of podcasts at no additional cost, and live streaming in partnership with Twitch. Engaging with music and culture has never been more natural, simple, and fun. For more information, visit amazonmusic.com or download the Amazon Music app.

Everyone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement. We are looking for new team members across a variety of job functions including software engineering/development, marketing, design, ops and more. Come join us as we make history by launching exciting new projects in the coming year.

Our team is focused on building a personalized, curated, and seamless music experience. We want to help our customers discover up-and-coming artists, while also having access to their favorite established musicians. We build systems that are distributed on a large scale, spanning our music apps, web player, and voice-forward audio engagement on mobile and Amazon Echo devices, powered by Alexa to support our customer base. Amazon Music offerings are available in countries around the world, and our applications support our mission of delivering music to customers in new and exciting ways that enhance their day-to-day lives.

About the Role

Love music? Want to help define the future of streaming and build innovative experiences that are used by millions of people every day?

We are seeking a Data Scientist to join the Amazon Music Fraud and Content Risk Management team. The team is responsible for protecting Amazon Music from a wide range of reputational and financial risks. We earn the trust of our customers and content creators by detecting and preventing risks such as copyright infringement, content policy violations, and streaming fraud.

As a Data Scientist, you will apply advanced analysis and statistical concepts to draw insights from massive datasets, create intuitive data visualizations, and build scalable machine learning models. You will work with product and program managers, software and business intelligence engineers, applied scientists, and business, legal, and industry relations leaders across the globe. Responsibilities include analysis of complex streaming and catalog datasets to make risk related decisions, creating visualizations to drive data insight, and developing scalable risk mitigation algorithms and models. You will have the opportunity to help build a program from the ground up, and deliver big and immediate results.

The ideal candidate is decisive, demonstrates good judgement in a variety of situations, is highly analytical, and is adept at synthesizing a variety of technologies and capabilities into high quality solutions. You should have an understanding of the digital music and/or digital risk mitigation landscape, or a demonstrated ability to quickly learn new industry domains. You must be able to thrive and succeed in an entrepreneurial environment and not be hindered by ambiguity. This means you are not only able to drive high-level strategic initiatives, but you also roll up your sleeves and get the job done when necessary.

LOCATION: There is flexibility for the location of this role. This role may sit in Atlanta or Seattle.

Basic Qualifications

  • Bachelor's Degree
  • 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
  • 2 years working as a Data Scientist
  • Experience applying various machine learning techniques, and understanding the key parameters that affect their performance

Preffered Qualifications

  • PhD in Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science, or a related quantitative field with at least 4+ years of working experience as a Data Scientist or related analytical positions.
  • Advanced knowledge and expertise with data modelling skills, advanced SQL for acquiring and transforming data.
  • Depth and breadth in quantitative knowledge. Excellent quantitative modeling, statistical analysis skills and problem-solving skills. Sophisticated user of statistical tools.
  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
  • Experience with causal inference, applied time series modeling or machine learning forecasting applications is a plus.
  • Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences.

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.

Support