Improving the quality of Apple user-facing products, such as Siri and Apple Intelligence, through principled evaluation and rigorous use of data, to deliver amazing search experiences across various Apple devices and languages.
Requirements
- Proficiency in data science, machine learning, and analytics, including statistical data analysis
- Experience crafting, conducting, analyzing, and interpreting experiments and investigations, especially on data quality, evaluation and risk assessment
- 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)
- Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data
- Worked with methods that address accuracy and variability in human annotation data
- Ability to learn new technology and skills to accommodate changing working requirements
- Experience with machine learning algorithms and user experience evaluations
Responsibilities
- Research and develop evaluation methods to improve the quality of Apple user facing products
- Work with evaluation/experimentation engineering teams to get methodological developments translated into technologies
- Work with large, complex data sets to solve difficult, non-routine analysis problems
- Apply advanced analytical methods, including prompt engineering and building LLMs as judges
- Conduct analysis that includes data collection and quality control, requirements specification, processing and presentations
- Build and prototype analysis pipelines iteratively to provide insights at scale
- Develop comprehensive knowledge of product data structures and metrics, advocating for changes where needed for product development
Other
- 5 years of relevant work experience
- Advanced degree in a quantitative field such as Statistics, Operational Research, Bioinformatics, Economics, Psychology, Computer Science, Sociology, Mathematics, Physics, or similar quantitative field
- Strong communication skills and the ability to naturally explain difficult technical topics to everyone from data scientists to engineers to business partners
- Proven ability to collaborate effectively across functions and work well within a team
- Capable of driving projects of varying sizes and scopes
