Data Scientist, Amazon

• 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

Desirable

• 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
• 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
• 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