Full Job Description
About this role In this role, you'll employ scalable 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. You'll leverage these technologies to analyze complex patterns in transaction data, identify anomalies, and create predictive models that can anticipate potential fraud before it occurs. Your work will be crucial in safeguarding the company's assets, protecting customers from financial harm, and maintaining the integrity of our systems. You'll translate intricate fraud patterns into actionable insights, enabling rapid response to emerging threats and informing critical business decisions related to risk management. You'll 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 an Applied Scientist, you will... - Protect Audible's customers and content creators against the onslaught of AI-generated fraud - Develop Amazon-scale data engineering & modeling pipelines. - Imagine and invent before the business asks, and create novel fraud detection and mitigation solutions using innovative approaches. - 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.
