Data Scientist - 24 month contract

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Sector: Journalism, Science and Pharmaceutical
Role: Professional
Contract Type: Permanent
Hours: Full Time

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
In this role, 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.

This position is for a 24 month contract.

ABOUT THE 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 Data Science (DS), 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...

1. Develop and validate models to optimize the Who, When, Where and How of all our interactions with customers
2. Develop Audible-wide data engineering pipelines
3. Imagine and invent before the business asks, and create groundbreaking applications using cutting-edge approaches
4. Open the Science black-box, use causal inference and develop compelling data visualizations
5. Work closely with other data scientists, ML experts, engineers and on cross-disciplinary efforts with other scientists within Amazon

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

1. Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
2. Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
3. 3 yrs relevant experience; or, PhD +1 yr relevant experience
4. MS in one of the following disciplines: Computer Science, Statistics, Data Science, Economics, Applied Mathematics, Operational Research or a related quantitative field
5. Experience in modeling, research design

PREFERRED QUALIFICATIONS

1. Experience in Python, Perl, or another scripting language
2. Experience in a ML or data scientist role with a large technology company

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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