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AIML - Sr Data Scientist, Evaluation

Apple

Salary not specified
Nov 15, 2025
Cupertino, CA, US
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Improving search quality and guiding feature development with data to deliver amazing search experiences across Apple products used by hundreds of millions of people globally

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 prompt engineering and building LLMs as judges

Responsibilities

  • Research and develop evaluation methods to improve the quality of Apple user facing products, such as Siri and Apple Intelligence
  • Work with evaluation/experimentation engineering teams to get methodological developments translated into technologies that product engineering will use every day
  • Work with large, complex data sets
  • Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed, 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
  • Proven ability to collaborate effectively across functions and work well within a team
  • Capable of driving projects of varying sizes and scopes
  • Strong communication skills and the ability to naturally explain difficult technical topics to everyone from data scientists to engineers to business partners