AIML - Data Scientist, Data and ML Innovation
Job Description
Summary
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 Siri, Search and Apple Intelligence engineering teams to improve product quality and guide feature development with data, to deliver amazing Apple Intelligence 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, Search 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 including LLM based approaches 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.
Minimum Qualifications
- Solid foundation in data science, machine learning, and evaluation, with hands-on experience in independently conducting and analyzing experiments. Ability to take ownership of smaller analytical projects and contribute effectively to larger initiatives.
- 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, and able to assist in prototyping data quality and evaluation pipelines, working alongside engineering teams to help solve data challenges.
- Some relevant internship or work experience for M.S. or Ph.D. candidates, or 3 years of relevant work experiences for people with other degrees in quantitative fields.
Preferred Qualifications
- Experience in generative model and application development, with a focus on data, evaluation, and automation.
- Ability to adopt or implement established methodologies and apply statistical analysis in problem-solving.
