Applied Scientist (m/f/d) in Berlin

Job summary
Good storytelling starts with great listening. At Audible, that means each role and every project has our audience in mind. Because the same people who design, develop, and deploy our products also happen to use them. To us, that speaks volumes.

ABOUT THIS ROLE
In this role, you will leverage your strong background in Computer Science, Machine Learning, and software engineering to build scalable solutions and innovative predictive modeling, ranking modeling (e.g. Search relevance and Recommendation), (un-) supervised learning, and simulation to 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
The Audible 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.

ABOUT YOU
We are looking for a motivated, results-oriented Applied Scientist with strong rigor and demonstrable skills in Machine Learning, Deep Learning, Natural Language Processing, data mining and/or large-scale distributed computation.

As an Applied 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, by adapting cutting-edge approaches or inventing new methods.
• 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.