The Data Scientist, AI/ML Model Quality role focuses on ensuring the integrity and quality of data that powers machine learning and generative AI systems at scale. You will build and maintain validation frameworks and monitoring pipelines to support the health of the data ecosystem across Wallet, Payments, and Commerce. This position requires collaboration with various teams including ML Engineering and Data Engineering to ensure that models are trained and evaluated on trustworthy data. The ideal candidate will have a strong background in data quality and statistical methods, contributing to the foundation of ML features that impact millions of users.

• A Bachelor's degree with hands-on experience in ML/AI model quality or a M.S or Ph.D in a related quantitative field is strongly preferred.
• 3+ years of experience in data science or a closely related analytical role with a focus on data quality.
• Proficiency in Python and SQL for complex data analysis and validation.
• Experience with distributed computing frameworks for analyzing large-scale datasets.
• Solid understanding of statistical methods including hypothesis testing and data drift detection.
• Experience in defining and tracking ML model health metrics in production.
• Familiarity with GenAI or LLM systems and their quality evaluation approaches.
• Strong communication skills to convey complex data findings to technical and non-technical stakeholders.
• Experience with data visualization tools to present ML telemetry.
• Familiarity with ML monitoring or observability platforms.
• Experience working with privacy-constrained data or under regulatory compliance frameworks.

• Build and maintain intelligent systems, validation frameworks, and monitoring pipelines.
• Ensure that every model is trained, evaluated, and deployed on trustworthy data.
• Collaborate closely with ML Engineering, Data Engineering, Privacy, and Legal teams.
• Define and analyze observability metrics to provide actionable product insights.
• Lead telemetry analysis across GenAI workflows.
• Own the health of the data ecosystem that supports ML and GenAI features.
• Translate raw quality signals into insights that drive real decisions.
• Monitor model performance and feature drift in production environments.

• 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.