Research and develop Responsible AI evaluation methods to improve the quality of Apple Intelligence's user facing products
Create evaluation data sets to solve difficult, non-routine analysis problems; applying sophisticated analytical methods as needed
Conduct analyses that includes data gathering and requirements specification, processing, analysis, ongoing work, and presentations
Build and prototype analysis pipelines iteratively to provide insights at large-scale
Develop extensive knowledge of data structures and metrics, advocating for changes where needed for product development
Partner closely with engineering teams on core machine learning algorithms and systems that are part of how features work
Minimum Qualifications
Strong programming skills: Including data-querying skills (SQL and/or Spark, etc.) and experience with a scripting language for data processing and development (e.g., Python, R, or Scala)
Proficiency in data science, machine learning, and analytics: Including statistical data analysis and A/B testing. Experience crafting, conducting, analyzing, and interpreting experiments and investigations
Experience articulating and answering business questions by applying statistical techniques to available data sources
Experience collecting and analyzing crowd-sourced data, language data, image data, and/or multi-modal data
Strong interpersonal skills: Proven ability to explain difficult technical topics (esp. causal topics) to everyone from data scientists to engineers to business partners
Work with highly-sensitive content with exposure to offensive and controversial content
Preferred Qualifications
Experience working in the Responsible AI space
Experience dealing with highly multi-labeled, nuanced, and often conflicting data sources
Ability to thrive in fast-paced environment, deal with uncertainty, and adapt to new and changing requirements
History driving projects of varying sizes and scopes - some will take months and some weeks — and you will need to cut through ambiguity and know when to dive deep
Advanced degree or equivalent experience in a quantitative field such as Statistics, Operations Research, Bioinformatics, Cognitive Science, Economics, Linguistics, Psychology, Computer Science, Sociology, Mathematics, Physics, or similar field
Proven track record of contributing to diverse teams in a collaborative environment
A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills
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