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 Senior Data Scientist, you will build scalable solutions and models to support our business functions (Marketing, Product, Content). 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 THE TEAM

Audible data science team partners with marketing, content, product, and technology teams 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), causal inference (CI) and GenAI / 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.

ABOUT YOU

We are looking for a motivated, results-oriented Data Scientist with strong rigor and demonstrable skills in ML, CI, NLP, data mining and/or large-scale distributed computation.

As a Senior 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 groundbreaking applications using cutting-edge approaches

• Develop compelling data visualizations

• Work closely with other data scientists, ML experts, engineers as well as business across globe, 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. Our Hub+Home hybrid workplace model gives employees the flexibility between gathering in a common office space (work from hub) and remote work (work from home). For more information, please visit adbl.co/hybrid

Basic Qualifications

• Modeling, research design experience and exposure to cutting-edge algorithms

• MS in one of the following disciplines: Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research or a related quantitative field and 6+ years relevant experience; or, PhD and 3+ years relevant experience

• Experience with methods for causal inference using longitudinal data and more generally (panel, regression, diff-in-diff, etc.)

• Fluency in English, both written and spoken

• Fluent in SQL, Python

• Exposure to software engineering environments (version control, command line...)

• Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions)

• Experience with Docker Container Platform

• Experience with machine learning methods for Bayesian estimation and inference

• Experience with Agile Software Development

Preferred Qualifications

• Domain knowledge of comparable products (marketing, digital, retail)

• Big Data Engineering with Spark / AWS EMR & Glue

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.