Job Description

At Audible, we don’t just tell stories—we empower them. Our team is on a mission to protect our millions of global listeners and content creators by revolutionizing the way we combat fraud. As an Applied Scientist, you’ll use cutting-edge machine learning (ML), deep learning (DL), and Natural Language Processing (NLP) to predict, detect, and prevent fraudulent activities at Amazon scale. You’ll be on the frontlines of building fraud defense mechanisms that not only safeguard Audible’s assets but also protect the heart of our platform: the customers and creators who make our audio world thrive.

If you’re ready to tackle real-world challenges with innovative solutions, work alongside some of the brightest minds, and help shape the future of fraud detection, this is your moment to make an impact!

What You’ll Do:

• Innovate & Protect: Develop groundbreaking fraud detection and mitigation solutions using state-of-the-art ML, DL, and NLP technologies.
• Predict & Prevent: Analyze complex patterns in transaction data, identifying anomalies and building predictive models that foresee fraud before it happens.
• Collaborate Globally: Partner with data scientists, ML experts, engineers, and business teams from around the world to solve complex challenges.
• Engineer at Scale: Design and build scalable data engineering and modeling pipelines using AWS tools like SageMaker, Batch, Lambda, and Step Functions.
• Lead & Learn: Contribute to the growth of the Audible Data Science team by sharing your insights, intellectual property, and learning from others in this collaborative environment.
• Shape Audible’s Future: Play a key role in safeguarding Audible’s platform, enabling us to continue delivering immersive, cinematic experiences to our listeners.

What You Bring:

• Master’s degree (or PhD) in Computer Science, Data Science, Statistics, Applied Math, or a related field + 5+ years of experience.
• Fluency in Python and SQL, with proficiency in languages like Java, C++, or similar.
• Expertise in machine learning algorithms and the ability to develop innovative solutions to real-world problems.
• Hands-on experience in ML pipeline orchestration using AWS (SageMaker, Lambda, Step Functions) or similar cloud platforms.
• Big Data engineering experience with tools like Spark, AWS EMR, or Glue.

Preferred Qualifications:

• Domain expertise in digital, retail, or similar industries.
• Publications in top-tier journals or conferences in NLP, deep learning, machine learning, or speech processing.
• A proven track record of innovation and developing novel algorithms that push the boundaries of what's possible in the field.

Why Audible?

• Innovative Environment: Work at the cutting edge of technology and fraud detection, making a real-world impact in the entertainment industry.
• Global Collaboration: Be part of a team that spans the globe, where every voice matters and diversity drives creativity.
• Creative Culture: At Audible, we believe in the power of storytelling—and our inclusive culture fosters creativity and empowers us to bring our best selves to work.
• Shape the Future: Join us and help redefine how Audible protects its global listeners and content creators from emerging fraud threats.