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.
About This Role
In this role, you'll 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.
Key Responsibilities:
* 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 groundbreaking fraud detection and mitigation solutions using cutting-edge 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
BASIC QUALIFICATIONS
* MS in one of the following disciplines: 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
* Experience in algorithm development
* Depth and breadth in state-of-the-art machine learning technologies
* Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
* Big Data Engineering with Spark / AWS EMR & Glue
PREFERRED QUALIFICATIONS
* Domain knowledge of comparable products (digital, retail)
* 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)
* Proven track record of innovation in creating novel algorithms and advancing the state of the art