AIML - Data Scientist, Evaluation

Do you get excited by driving product impact via measurement and evaluation, for products and services used by hundreds of millions of people globally? Within the evaluation organization, the mission of Data Science and Insights team is to guide product development, decisions and directions through principled evaluation and rigorous use of data. You will partner with various 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. ## Description 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 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, 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. 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. ## Minimum qualifications PhD in Statistics, Mathematics, Econometrics, Economics, Operations Research, Computer Science, or related field and 1+ year(s) data-science experience or Master's Degree in Statistics, Mathematics, Econometrics, Economics, Operations Research, Computer Science, or related field and 3+ years data-science experience. 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. Strong communication skills and the ability to naturally explain difficult technical topics (especially causal topics) to everyone from data scientists to engineers to business partners. ## Preferred qualifications Proven ability to collaborate effectively across functions and work well within a team. Capable of driving projects of varying sizes and scopes - some will take months and some weeks — and you will need to know when to dive deep. Worked with methods that address accuracy and variability in human annotation data. Ability to learn new technology and skills to accommodate changing working requirements.