Sr. Data Scientist, Apple Business & Education Organization

The Business and Education team builds cloud and software solutions for organizations, such as Apple Business Manager - device management, Managed Apple Accounts, and app distribution for organizations, plus the brands and locations that shape how businesses appear across Maps, Siri, and Spotlight.

The Business & Education Data Organization embeds data-informed thinking into every decision. You’ll partner with product, engineering, and business teams to generate insights, measure impact, and guide strategy across our services., We’re seeking an experienced Senior Data Scientist to drive high-impact analytics for Apple’s business and education services. You’ll collaborate across engineering, product, and business teams to uncover opportunities, optimize experiences for organizations, and influence decisions at global scale.

This role requires technical depth, strategic thinking, and strong communication. You’ll deliver insights that shape Apple’s business and education offerings, lead complex analytical projects, and expand a culture of data-informed decision-making., * 7+ years in data analytics or data science; 5+ years applying statistical modeling or ML in production.

• Proven ability to influence cross-functional initiatives using data-informed insights.
• Strong communicator skilled at framing complex concepts for senior audiences.
• Deep expertise in product analytics, launch reporting, and impact measurement.
• Proficiency in SQL and Python/R with strong statistical and experimental design foundations.
• Experience structuring ambiguous problems and delivering actionable insights.
• Experience with generative AI or ML-based agents for automating analytical workflows and building data products at scale., * Advanced degree in quantitative field (Statistics, Mathematics, Computer Science, Engineering, Economics or related disciplines).
• Experience with B2B or enterprise products - understanding how building for organizations differs from consumer products.
• Practical experience with experimentation and advanced causal inference methods.
• Hands-on experience with large-scale data ecosystems (Hive, Spark, Presto).
• Demonstrated success influencing or leading projects within matrixed, cross-functional environments.