Use data intuition to translate hard product goals and business problems into solvable data science problems
Design, create and validate actionable metrics, at both the component level and to measure overall user engagement and experience
Work with human-labeled datasets and relevance judgments to evaluate ranking algorithms
Conduct exploratory data analyses to mine large volume of data, extract insights, and recommend opportunities for search product improvements
Automate analyses and pipelines via SQL and Python-based ETL frameworks
Communicate insights to partner teams to influence product direction with data
Build data products (feature datasets, analyses, models, etc.), dashboards and automation to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management
MS/PhD in Computer Science, Statistics, Physics, Operations Research, or similar quantitative domain
3+ years experience with data analysis at web scale or relevant work experience
Proficient in Python
Proficient in at least one database language (e.g., SQL, Snowflake)
Capable of translating business questions and needs into technical requirements, and using statistical techniques to find solutions
Solid communication and presentation skills
Prior work experience with human-labeled datasets
Experience assessing the quality of unreleased product features
Prior proven industry experience with large data sets using technologies like Hadoop and Spark
Experience writing pipelines for automating analytics tasks at scale
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.