Data Scientist, SAMBA
DESCRIPTION
At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.
ABOUT THIS ROLE
As a Data Scientist, you will build scalable solutions and models to support our business functions (Content, Marketing, Product). Leveraging a range of methods including machine learning and simulation, you will explain, quantify, predict and prescribe in support of informing critical business decisions. You will translate business goals into agile, insightful analytics. You will seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders.
ABOUT THIS TEAM
Audible's Data Science team partners with Marketing, Content, Product, and Technology partners to solve business and technology problems using scientific approaches to build product and services that surprise and delight our customers. We employ scalable cutting-edge machine learning (ML), deep learning (DL), and Natural Language Processing (NLP) knowledge to better target customers and prospects, understand and personalize the content, and context needed to optimize their book-listening experience. We operate in an agile environment in which we own and collaborate on the life cycle of research, design, and model development of relevant projects.
As a Data Scientist, you will...
- Develop and validate models to optimize the Who, When, Where and How of all our interactions with customers
- Develop Amazon-scale data engineering pipelines
- Imagine and invent before the business asks, and create applications using cutting-edge approaches
- Open the Science black-box, use causal inference and develop compelling data visualizations
- Work closely with other data scientists, ML experts, engineers and on cross-disciplinary efforts with other scientists within Amazon
- Contribute to the growth of the Audible Data Science team by sharing your ideas, intellectual property and learning from others
ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
BASIC QUALIFICATIONS
- 3 yrs relevant experience, and MS in one of the following disciplines: Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research or a related quantitative field, or PhD +1 year of relevant experience
- Fluent in SQL, Python
- Modeling, research design experience
- Experience in Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
- Experience in Big Data Engineering with Spark / AWS EMR & Glue
- Experience with Agile Software Development
PREFERRED QUALIFICATIONS
- Domain knowledge and expertise of paid marketing, specifically in Paid Search and Organic Search
- Experience with Container Platforms (Docker, Kubernetes/Fargate)
- Experience with Streaming data processing
- Experience with R, RShiny, and Scala
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.
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.