Data Scientist, ML Quality & GenAI Observability

Apple, Inc.; New York (NY); On-site; USD 150,000 - 278,000; Full time

Benefits offered by this job

Medical & dental benefits

Employee stock programs

Tuition reimbursement

Relocation assistance

Job summary

Apple Inc. in New York City is seeking a Data Scientist, AI/ML Model Quality, to own the health of training data and observability for ML/GenAI across Wallet, Payments, and Commerce. Build validation frameworks and telemetry to ensure models are trained, evaluated, and deployed on trustworthy data.

You will collaborate with ML Eng, Data Eng, Privacy, and Legal to surface actionable insights and drive model health across GenAI systems powering hundreds of millions of users.

Qualifications

• Bachelor's or higher in a quantitative field strongly preferred.
• 3+ years in data science or related analytical role.
• Proficient in Python and SQL for analysis and validation.
• Experience with distributed computing (PySpark/Spark).
• Strong data quality, model evaluation, or ML observability background.

Responsibilities

• Curate, analyze, and maintain ground-truth datasets for model evaluation.
• Audit training data for bias and fairness; monitor data drift.
• Define and report data quality metrics for leadership audiences.
• Design automated data quality rules with Data Engineering integration.
• Define ML observability metrics and translate signals into insights.
• Develop dashboards and reporting for real-time model health across ML/GenAI.
• Analyze telemetry across GenAI workflows and track quality signals.
• Identify degradation patterns and advise model/data teams with concrete steps.

Skills

Python (Pandas, NumPy, Scikit-learn)

SQL

PySpark / Spark

Data quality & validation

ML observability

GenAI / LLM familiarity

Communication skills

Education

Bachelor's degree

MS/PhD preferred

Tools

Tableau

Apache Superset

Databricks

LangSmith

MLflow

Weights & Biases

Job description

Apple Inc. in New York City is seeking a Data Scientist, AI/ML Model Quality, to own the health of training data and observability for ML/GenAI across Wallet, Payments, and Commerce. Build validation frameworks and telemetry to ensure models are trained, evaluated, and deployed on trustworthy data.

You will collaborate with ML Eng, Data Eng, Privacy, and Legal to surface actionable insights and drive model health across GenAI systems powering hundreds of millions of users.