Audible is looking for Data Scientists to drive innovation in understanding the incremental impact and value of product features and marketing strategies. The role aims to implement test designs and evaluations of new product launches, promotions, and media campaigns to understand business impact across all sales channels, ultimately creating value for stakeholders and customers.
Requirements
- Experience in understanding of standard data structures, algorithms, and software development
- Fluency in Python, SQL or similar scripting languages
- Algorithm development experience
- Breadth in ML technologies
- Experience in employing LLMs/GenAI to solve problems
- 1+ years of industry experience in Deep Learning, Natural Language Processing/Understanding, Reinforcement Learning and/or GenAI
- Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
Responsibilities
- Analyze customer data for segmentation, clustering, acquisition, retention, engagement, and recommendations
- Perform content evaluation, apply natural language processing, analyze attributes and representations (in text, audio, cover art), generate content recommendations, and identify trends
- Conduct product-related analyses including user click stream analysis, search engine optimization, and product recommendations
- Evaluate marketing performance across earned, paid, and owned media evaluation
- Implement test designs and evaluations of new product launches, promotions, and a mix of media campaigns
- Develop advanced scientific solutions
- Engage in cutting-edge research to solve business problems
Other
- MSc in one of the following disciplines: Computer Science, Computer Engineering, Machine Learning, Data Science, Applied Math, or a related quantitative field
- PhD in one of the following disciplines: Computer Science, Computer Engineering, Machine Learning, Data Science, Applied Math, or a related quantitative field
- Experience with Agile Software Development
- Experience with programming in at least one compiled programming language such as Java, C++, C-Sharp
- Publications at top-tier peer-reviewed conferences or journals
