Data Scientist - Wallet, Payments & Commerce

Every day, millions of people rely on Apple Pay and Wallet to make life simpler, safer, and more connected. Behind each seamless tap is a complex ecosystem that must be reliable, scalable, and trusted. Our mission is to ensure these experiences not only work flawlessly but continue to improve through data, innovation, and system excellence.

Description

The Wallet, Payments & Commerce (WPC) Operations Data Science team drives this mission. We combine technical depth with operational insight to measure, diagnose, and improve product performance across billions of transactions. As a Data Scientist, you'll build the intelligence that powers global commerce - from anomaly detection and forecasting to dashboards that guide engineering and operations. Working with teams across Apple, your insights will shape the future of payments and impact millions worldwide.

Responsibilities

• You are a dedicated data scientist who loves working with people across technical and non-technical domains to solve problems and deliver results.
• In this role, you will build models to detect anomalies, forecast outcomes, and apply causal inference to connect system changes to customer and business impact.
• You will design and analyze experiments to guide product and engineering decisions, partner across product, engineering, and operations to embed data-driven thinking into roadmaps, and apply advanced methods - including NLP, LLMs, and GenAI where valuable - to improve diagnostics and partner self-service.
• Most importantly, you will turn complex data into clear, actionable insights that shape how Apple Pay and Wallet evolve at global scale.

• 3-5 years of experience in data science, business analytics, or BI.
• Ability to extract meaningful business insights from data and identify the stories behind the patterns.
• Understanding of statistical concepts and practical experience applying them (in anomaly detection, forecasting, causal inference, NLP etc.).
• Expert level SQL with advanced Snowflake performance tuning expertise.
• Python development experience with pandas and NumPy.
• Communication skills for presenting complex quantitative analyses to senior business executives.
• Bachelor's degree required in quantitative field (Data Science, Applied Econometrics, Statistics, Machine Learning, Analytics, Mathematics, Operations Research, or related).

• Strong critical thinking and interpersonal skills with the ability and desire to learn and evaluate new technologies.
• Self-directed and proactive. You thrive in an ambiguous and fast-paced environment.
• Advanced degree (Master's/PhD) preferred in quantitative field (Data Science, Applied Econometrics, Statistics, Machine Learning, Analytics, Mathematics, Operations Research, or related field).
• Proven understanding of machine learning, deep learning and natural language (including LLMs) processing and ability to optimize machine learning models to adapt to solving various kinds of issues.