Senior Fraud Detection Specialist

We are seeking a highly skilled Senior Applied Scientist to join our team at Audible, a leading producer and provider of audio storytelling. As a key member of our data science team, you will play a critical role in developing and implementing cutting-edge machine learning and deep learning techniques to detect and prevent fraudulent activities.

As a Senior Applied Scientist, you will be responsible for designing and implementing scalable machine learning pipelines to analyze complex patterns in transaction data, identify anomalies, and create predictive models that can anticipate potential fraud before it occurs. You will work closely with other data scientists, ML experts, engineers, and business stakeholders to develop and deploy innovative solutions that drive business value and protect our customers and content creators from financial harm.

• Design and implement scalable machine learning pipelines to detect and prevent fraudulent activities
• Analyze complex patterns in transaction data to identify anomalies and create predictive models
• Work closely with other data scientists, ML experts, engineers, and business stakeholders to develop and deploy innovative solutions
• Contribute to the growth of the Audible Data Science team by sharing knowledge, ideas, and best practices

Audible is a global company with an entrepreneurial spirit, passionate about the positive impact we can make for our customers and our neighbors. We are dreamers and inventors who are committed to building more equitable communities in the cities we call home. Our mission is to spark listeners' imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers' daily lives.

• MS in Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research, or a related quantitative field + 5 years of relevant experience; or PhD
• Fluency in Python, SQL, or similar scripting languages and skilled at Java, C++, or other programming languages
• Experience in algorithm development and machine learning pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
• Big Data Engineering with Spark / AWS EMR & Glue

• 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