Short DescriptionApple is looking for Siri-Data Scientist who will build analytic, visualization, and other information products with a drive to automate and scale the insights available to science and engineering teams.
- You will partner closely with Siri engineering teams to develop ways of characterizing the user experience in how Siri executes on requests and connecting those characterizations into Siri's development.
- Define metrics that we will measure our efforts against as well as defining the instrumentation required for yielding sufficient data.
- Communicate with an advocate to a wide audience of engineers, managers, and executives to inform decisions on how Siri evolves.
- Build analytic, visualization, and other information products with a drive to automate and scale the insights available to science and engineering teams.
- Perform exploratory data analyses to enrich our mental models about Siri usage and identify new questions to pursue.
- Extract information from structured and unstructured data coming from Siri's computational architecture.
- You think about data in terms of statistical distributions and have a big enough analytics toolbox to know how to find patterns in data, identify targets for performance, and identify sources of variance about those targets.
- You use good judgment balancing art and science when visually communicating information (e.g. Tableau, Superset, ggplot, D3).
- You have engineered information out of massive and complex datasets (e.g. Hive, Spark, Druid, Solr, Oozie).
- You have proven experience with at least one programming language (e.g. Python, R, Scala) and are comfortable developing code in a team environment (e.g. git, notebooks, testing).
- You are self-motivated and curious with demonstrated creative and critical thinking capabilities and an innate drive to improve how things work.
- You have a high tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.
- You have excellent verbal and written communications skills and experience in influencing decisions with information.
- Your academic background is in a quantitative field such as Computer Science, Statistics, Engineering, Economics or Physics. Advanced degree preferred.