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. You will build and maintain validation frameworks and monitoring pipelines to support the health of the data ecosystem across Wallet, Payments, and Commerce. Collaborating with various teams, you will define observability metrics and lead telemetry analysis to ensure high-quality data for model training and evaluation. This position is crucial for delivering exceptional ML features to millions of users.

• Bachelor's degree with hands-on experience in ML/AI model quality or a M.S or Ph.D in a related quantitative field.
• 3+ years of experience in data science or a closely related analytical role.
• Proficiency in Python and SQL for complex data analysis.
• Experience querying and analyzing large-scale datasets using distributed computing frameworks.
• 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.
• Strong communication skills to convey complex data findings.
• Experience with data visualization and dashboarding tools.
• Familiarity with LLM evaluation frameworks and synthetic data generation techniques.
• Experience with ML monitoring or observability platforms.
• Experience working with privacy-constrained data or under regulatory compliance frameworks.
• Background in financial services, fintech, or consumer payment products.

• Build and maintain intelligent systems and validation frameworks.
• 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 surface actionable product insights.
• Lead telemetry analysis across GenAI workflows.
• Own the health of the data ecosystem that underpins ML and GenAI features.
• Translate raw quality signals into insights that drive real decisions.
• Monitor and evaluate the performance of ML models in production.

• 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.