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. In this role, youll employ scalable cutting-edge machine learning (ML), deep learning (DL), and Natural Language Processing (NLP) techniques to detect and predict fraudulent activities, enhance fraud investigation capabilities, and develop advanced fraud protection and defense mechanisms. Youll leverage these technologies to analyze complex patterns in transaction data, identify anomalies, and create predictive models that can anticipate potential fraud before it occurs. Youll operate in an agile environment in which we own and collaborate on the life cycle of research, design, and model development of relevant projects.
Protect Audible’s customers and content creators against the onslaught of AI-generated fraud
* Develop Amazon-scale data engineering & modeling pipelines
* Work closely with other data scientists, ML experts, engineers as well as business across the 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
Audible is the leading producer and provider of audio storytelling. 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. Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research or a related quantitative field +5 yrs relevant experience; or PhD
* Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programing languages
* Big Data Engineering with Spark / AWS EMR & Glue PREFERRED QUALIFICATIONS
* Publications at top-tier peer-reviewed conferences or journals in one of those areas (natural language processing/understanding, deep learning, machine learning, or speech processing)
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