Data Scientist @ Audible - Newark, NJ

Job Overview

a month ago

Data Scientist

Audible - Newark, NJ

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.

Audible is searching for an exceptional data scientist to join our economics team and drive the development of models at the intersection of machine learning and econometrics at scale. The Audible economics organization works across the business to measure and maximize the value Audible delivers to customers, creators, and communities globally. In this role, there will be a focus on partnering with our content and product teams to build a groundbreaking catalog of audiobooks and spoken-word entertainment, develop innovative tools to generate value for creators, and optimize content distribution and monetization.

We are looking for someone experienced in building ML models at scale for complex prediction and optimization problems, who also has a background (or burgeoning interest!) in causal inference or interpretable machine learning. In addition to working with our staff economists and data scientists, you will also collaborate closely with scientists across Audible and partner teams at Amazon on problems pertinent to subscription businesses and the production of original media content.

As a Data Scientist, you will...
  • Work with leadership in 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 and maintain scalable, innovative data science and machine learning models that deliver actionable insights and results.
  • Collaborate with other data scientists, economists, and analysts at Audible to build data-driven solutions to key business problems.

Basic Qualifications

  • PhD, MS or Bachelor’s degree in Statistics, Economics, Machine Learning, Operations Research, Computer Science, Applied Mathematics, or another quantitative field. (If MS degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 4+ years of proven experience required)
  • Fluent in mathematical foundations of statistics, machine learning, and economics.
  • Experience formulating and solving challenging optimization problems.
  • Strong experience using Scala, Python or R, SQL and Spark to work efficiently at scale with large data sets.
  • Experience in building and evaluating algorithms and optimizing for performance in production.

Preferred Qualifications

  • Knowledge of causal ML methods, such as high-dimensional models, double/debiased ML, causal random forest, matrix completion methods.
  • A record of research publication in journals or speaking at conferences in a technical area, such as Machine Learning, Statistics, Operations Research, or Computer Science.
  • Experience in using data science and ML to inform pricing, investment, development, or production of original media content.
  • Experience working on a cross functional team, including with product managers, software and data engineers.

At Audible, we innovate and inspire through the power of voice. We're changing the narrative on storytelling. As a leading creator and provider of premium audio storytelling, we've redefined the ways people access, discover, and share stories. The stories we tell have the ability to transport and transform everyday moments into meaningful experiences and it's our people who make Audible's service possible. We're listeners, storytellers, and problem-solvers. Our perspectives and experiences power our ideas and come together in our mission to unleash the power of the spoken word.

Audible is committed to a diverse and inclusive workplace. Audible is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

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