Sr. Data Scientist Amazon
Seattle, WA

Job Description

Amazon Music

Imagine being a part of an agile team where your ideas have the potential to reach millions. Picture working on cutting-edge consumer-facing products, where every single team member is a critical voice in the decision-making process. Envision being able to leverage the resources of a Fortune-500 company within the atmosphere of a start-up. Welcome to Amazon Music, where ideas are born and come to life as Amazon Music Unlimited, Prime Music, and so much more.

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.

Come innovate with the Amazon Music team!

As a Senior Data Scientist in Music, you'll discover insights that drive marketing, content and product strategy for our Amazon Music streaming service. You will have the opportunity to work with a huge and rapidly growing data set generated by mobile, desktop and home music streaming application usage interactions and music consumption behaviors.

As a successful data scientist at Amazon Music, you need to understand the streaming music industry and the meanings of data across Marketing, Product, Finance, Curation and Content. You will expose and measure current performance in marketing acquisition and product engagement. You will identify specific and actionable opportunities to solve existing business problems at Amazon Music, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user of advanced quantitative techniques for answering specific business questions, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication.

Major responsibilities include:

Translate / Interpret

* Complex and interrelated datasets describing customer behavior, messaging, content, product design and financial impact.

Measure / Quantify / Expand

* Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
* Analyze historical data to identify trends and support decision making.
* Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
* Provide requirements to develop analytic capabilities, platforms, and pipelines.
* Apply statistical or machine learning knowledge to specific business problems and data.

Explore / Enlighten

* Formalize assumptions about how users are expected to behave, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.
* Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
* Make Decisions and Recommendations
* Build decision-making models and propose solution for the business problem you defined
* Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
* Utilize code (Python/R/SQL) for data analyzing and modeling algorithms