The Product Data Science team at Apple Services Engineering is seeking a scientist to develop and deploy machine learning solutions for partner-facing analytics applications. This role involves building algorithms that enhance content-partner analytics tools and contribute to Apple's global content charts. The team emphasizes a strong connection to research, focusing on privacy-preserving analytics and experimentation engines. Candidates should be passionate about solving high-impact problems at scale and translating research into practical features.

• MS or PhD in Statistics, Computer Science, Machine Learning, or a related quantitative field, or equivalent industry experience.
• 3-5+ years of industry experience designing and deploying ML or statistical solutions in production.
• Proficiency in multiple ML domains including supervised and unsupervised learning, deep learning, time-series modeling, and Bayesian statistics.
• Experience with differential privacy, causal inference, or statistical experimentation such as A/B testing.
• Production engineering experience in Python, and familiarity with Scala or Spark.

• Develop and deploy end-to-end machine learning solutions in production.
• Frame problems, design algorithms, and manage the full deployment lifecycle.
• Build and maintain the intelligence layer behind partner-facing analytics applications.
• Translate research into features that provide useful insights for content partners.
• Communicate effectively with both technical and non-technical audiences.

• 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.