Data Scientist, Content & Audience

Key Skills

Java Programming, Design, Python Programming, SQL, Scala Programming, R Programming, Shell Scripting language, SPARK Programming, AWS Sagemaker, Econometrics, Object-Oriented programming (OO languages)

Job Description

Job summary

Good storytelling starts with great listening. At Audible, that means each role and every project has our audience in mind. Because the same people who design, develop, and deploy our products also happen to use them. To us, that speaks volumes.

ABOUT THIS ROLE

Audible seeks an exceptional data scientist to work on modeling at the intersection of audience and content strategy. As a Data Scientist, Content & Audience, you will work to help partner teams in Content, Product, and Marketing better understand our audience and create optimized strategies for content investment, distribution, marketing, and discovery – driving value for both customers and the business.

As a Data Scientist, you will...

• Work with our Content and Product organizations to identify key analytical problems and opportunities – your work is expected to be a key input to our future content strategy.
• Develop, validate, scale, and maintain innovative models that deliver actionable insights.
• Identify and source novel data to leverage in modeling work – both from within Audible/Amazon and from 3P sources.
• Collaborate with other data scientists, analysts, economists, and engineers at Audible/Amazon to build data-driven solutions to key business problems.

BASIC QUALIFICATIONS

• Bachelor’s degree in Computer Science, Statistics, Data Science, Applied Mathematics, or related field.
• 2+ years of experience (at least 1 year in industry) applying ML techniques to large datasets.
• Experience in programming languages/platforms: fluency in Python, R, SQL, Spark.
• Experience building rigorous ML models at scale for complex prediction and optimization problems.
• Experience working cross-functionally with analysts, engineers, product managers, etc.

PREFERRED QUALIFICATIONS

• Background (or burgeoning interest!) in causal inference techniques and/or Natural Language Processing.
• Experience with unsupervised learning problems (e.g., multidimensional clustering).
• MS or PhD in one of the above disciplines.
• Domain knowledge of comparable products (digital, retail).
• Experience with causal inference techniques, econometrics, and/or causal ML methods (e.g., double/debiased ML, causal random forest, etc.).
• Experience presenting complex technical information to laypeople.
• Experience with Scala.
• Familiarity with AWS services.
• Passion for data (and fearlessness in the face of a data tsunami), modeling, research design and cutting-edges algorithms.
• Strong data presentation skills.
• Ability to learn quickly and structure ambiguous problems.