The Product Data Science team at Apple Services Engineering focuses on building statistical, ML, and AI-powered algorithms for various digital platforms. This role seeks a scientist experienced in deploying end-to-end ML solutions in production, with a strong emphasis on high-impact problem solving. The team is dedicated to translating research into practical features that provide valuable insights to content partners and enhance user experience. Candidates will work on projects involving experimentation engines, privacy-preserving analytics, and partner-facing applications.

• MS or PhD in Statistics, Computer Science, Machine Learning, or a related quantitative field.
• 3-5+ years of industry experience designing and deploying ML or statistical solutions in production.
• Proficiency in Python for production-quality software engineering.
• Experience with differential privacy, causal inference, or statistical experimentation.
• Familiarity with distributed data platforms and web-scale pipelines.

• Build and deploy end-to-end ML solutions in production.
• Develop algorithms for content-partner analytics tools and experimentation engines.
• Translate research into features that provide useful insights for content partners.
• Communicate findings clearly to both technical and non-technical audiences.
• Collaborate with cross-functional teams in a geographically distributed environment.

• 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.