The Senior Machine Learning & Data Scientist role at Apple focuses on analyzing high dimensional data to derive insights that can impact millions of users. The position requires a proactive engineer with strong machine learning and analytical skills to develop data products that enhance Apple's software and hardware performance. The successful candidate will work collaboratively across teams to influence decisions and provide meaningful insights. A strong foundation in statistical analysis and software engineering is essential for success in this role.

• M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a similar quantitative field.
• Strong quantitative foundation with expertise in statistical analysis and practical machine learning.
• Proficiency in distributed compute and storage technologies such as HDFS, S3, Iceberg, Spark, and Trino.
• Experience designing ETL flows and automation/scheduling using tools like Kubernetes and Airflow.
• Strong interpersonal skills and the ability to build relationships with diverse stakeholders.

• Analyze high dimensional data to derive meaningful insights.
• Produce metrics, models, simulations, and tools for analysis and communication of insights.
• Transform raw data into actionable insights through practical problem formulation and ETL processes.
• Drive cross-functional projects with diverse sets of stakeholders.
• Connect data insights to the company's overall strategy and objectives.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.