Data Scientist, Apple Media Products

    • Cupertino, CA


Posted: May 21, 2020

Role Number: 200161835

The Apple Media Products Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. These are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And they do it on a massive scale, meeting Apple's high expectations with high performance to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. These engineers build secure, end-to-end solutions. They develop the custom software used to process all the creative work, the tools that providers use to deliver that media, all the server-side systems, and the APIs for many Apple services. Thanks to Apple's unique integration of hardware, software, and services, engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, nimble, and multi-functional, offering greater exposure to the array of opportunities here. Do you want to make impact on how decisions are made by Engineering teams? If you love statistics, data, analysis and influencing teams on how to run experiments then look no further. This team in the Apple Media Products group provides insights through data that drive decision-making for our engineering and product teams. We are looking for a Data Scientist that can derive valuable insights and help us build automated reporting tools from the data we collect on AppStore, Apple Music, Movies & TV, etc. This role will be working daily with researchers and engineers on the Search and Recommendations teams as they develop better algorithms and improve their models. This in turn improves the customer experience for Apple's products. You will be helping to drive innovation and improve the way we make decisions while developing new experimentation methodologies, statistical techniques, and causal-inference approaches.

Key Qualifications

  • Five or more years relevant industry experience required.
  • Extensive knowledge in statistical methods and data mining.
  • Excellent application skills in experimentation methodologies and causal inferences.
  • Experience with common data science toolkits, such as R/Python and libraries like pandas, dplyr and ggplot.
  • Proficiency in using query languages such as SQL and Hive.
  • Experience with Big Data systems and distributed computing, such as Hadoop and Spark.
  • Excellent communication skills with the ability to explain findings in layman terms and influence decision makers.
  • Attention to data detail with regards to quality, transformation and potential impact.


You will design, execute and craft tools for online experiments (A/B tests) and offline experiments (human relevance judgement) that help us improve and fine tune our data focused features (Search, Recommendations, etc.). Your primary focus will be on applying statistical methods, developing A/B testing procedures, and automating data pipelines to develop new metrics. In this role you will: Work with engineering teams to improve data collection procedures. Process, clean, and verify the integrity of data. Investigate new sources that can extend and improve our insights. Design experiments that will measure and test for key performance indicators. Model and analyze data using state-of-the-art methods. Generate reports (that can be automated) to present key insights to partners across a variety of teams. Drive end-to-end data applications to address business needs.

Education & Experience

Master's Degree in Computer Science, Statistics, Applied Math or related discipline. PhD preferred.

Additional Requirements

Back to top