Data Scientist – Student Position – Sales Business Analytics

Role Overview

As a Data Scientist – Student Position, Sales Business Analytics in Apple’s Sales organization, you’ll play a key role in supporting our mission by delivering operational excellence through data insights, reporting, analytics, and tools to advance our strategic vision.

What You Will Do

Your work will center on a subset of the following: Data Pipeline Modernization and Observability, Workflow Orchestration and Tooling Migration, AI Agent Development and Evaluation, Analytics, Modeling, and Tiering, Data Governance and Enablement, and Collaboration and Cross-Functional Impact.

Why It Might Be a Fit

This program offers mentorship and development to elevate your business acumen and give visibility to a wide spectrum of business projects at Apple. You will be embedded within a Sales Data and Analytics team and will own deliverables end to end.

Requirements

• Enrolled in a Bachelor’s or Master’s program in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field
• Strong proficiency in Python and standard data libraries (pandas, NumPy)
• Strong command of SQL and relational database concepts, including experience with PostgreSQL & Snowflake or a comparable relational database
• Hands-on experience building end-to-end data pipelines or applications
• Experience with Git and collaborative version control workflows
• Foundational understanding of algorithms, data structures, and software engineering design
• Demonstrated AI literacy: familiarity with how LLMs work, their failure modes, and where they are and are not appropriate
• Strong communication and writing skills

Benefits

• Mentorship and development to elevate business acumen
• Visibility to a wide spectrum of business projects at Apple
• Embedded within a Sales Data and Analytics team
• Opportunity to work on a subset of the following: Data Pipeline Modernization and Observability, Workflow Orchestration and Tooling Migration, AI Agent Development and Evaluation, Analytics, Modeling, and Tiering, Data Governance and Enablement, and Collaboration and Cross-Functional Impact