Audible is seeking a data scientist to tackle a wide range of economic and product-related questions, including pricing, experimentation science, data-driven product strategy/optimizations, internal productivity/incentives, audience science, and impact/ROI measurement. The goal is to leverage data-driven insights to shape the future of digital media.
Requirements
- 1+ year hands-on work experience in an applied/industry setting using SQL and Python, or similar, to work efficiently at scale with large data sets, constructing empirical analysis, modeling, and compelling data visualizations
- Experience formulating and solving challenging optimization and/or measurement problems
- Fluency in mathematical foundations of statistics, machine learning, and economics
- Experience using empirical methods to inform pricing, investment decisions, experimentation science, and/or product optimizations in the digital media space
- Ability to tackle very loosely defined problems and consistently deliver elegant, modular, and scalable solutions in a timely manner
Responsibilities
- Develop innovative descriptive analysis, modeling, and experimental approaches to drive actionable insights
- Build data pipelines, and identify novel data sources to leverage in analytical work – both from within Audible/Amazon and from 3P sources
- Force multiply the work of the team with compelling data visualizations, presentations, and/or dashboards to drive awareness and adoption of data assets/products/insights
- Raise the bar for science/analytical work, both within Audible and across the broader Amazon community
- Work with Product, Content, and Marketing partners to identify key analytical problems and opportunities, and collaborate with other data scientists, economists, and analysts to construct data-driven solutions
Other
- Undergraduate degree in: Statistics, Economics, Computer Science, Engineering, Applied Math, or a similar/related quantitative field
- Graduate-level training in one of the above mentioned fields
- Experience working on a cross functional team, including product managers, marketers, and software/data engineers
- Familiarity with financial/accounting metrics/methods
- Intellectual curiosity for what drives the business and strong desire to continue to learn new tools and empirical methods
