Do you get excited by driving product impact via measurement and evaluation, for products and services used by hundreds of millions of people globally? The vision for the AIML Data organization is to improve products by using data as the voice of our customers. Within this organization the mission of the Search Analytics team is to inform product evolution through measurement, evaluation, and analysis of the user experience. You will partner with Search engineering teams to improve search quality and guide feature development with data, to deliver amazing search experiences across iPhone, iPad, HomePod, Mac, Watch, tv, across dozens of languages.

Research and develop evaluation methods to improve the quality of Apple user facing products, such as Siri and Search. Work with evaluation/experimentation engineering teams to get your 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. 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. Partner closely with product engineering teams on core machine learning algorithms and user experience evaluations. You should be passionate about building outstanding products. This position involves a wide variety of skills and innovation.

Proficiency in data science, machine learning, and evaluation. Experience crafting, conducting, analyzing, and interpreting experiments and investigations. Proven ability to independently lead large-scale, open-ended analytical projects.Proficiency in critical thinking, problem-solving, and collaboration with cross-functional teams to address business needs. Strong communication skills for articulating and translating business questions into actionable insights using statistical techniques and available data.Strong programming skills in Python for data processing, with expertise in SQL or Spark. Proficient in data wrangling, prototyping data quality and evaluation pipelines for new methodology development, and building scalable solutions in collaboration with engineering teams to solve complex data challenges.5 years of relevant work experience for M.S. or Ph.D. candidates, or 8 years of relevant work experiences for people with other degrees in quantitative fields.