Manager Data Products & AI Analytics - Supply Chain Operations - BPR

Summary

At Apple, we rely on our employees diverse set of backgrounds and perspectives to champion innovation through extraordinary ideas to surprise and delight our customers. These ideas can come from anywhere. Will that next phenomenal idea come from you?

Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple’s Information Systems and Technology (IS&T) organization. IS&T is the engine behind everything Apple does for customers and for the people who build for them. It’s Apple’s central nervous system. Supporting 2.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS&T makes the impossible feel effortless.”

Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here.

Description

Our BPR team is looking for a Manager – Data Products & AI Analytics to lead a team that turns Apple's supply chain data into trusted, AI-ready analytics. You will combine deep supply chain functional credibility with technical judgment. You will build and grow a team, set its direction, and make sure it delivers decisions, not just dashboards, across Planning, Operations, Logistics, Manufacturing, and Fulfillment.

This is a highly visible role. You will be the primary link between business leaders, technology partners, and an analytics team that may span multiple locations.

Preferred Qualifications

Experinece in supply chain product development
Master's degree in Supply Chain, Industrial Engineering, Operations Research, Computer Science or Analytics, or equivalent experience.

Minimum Qualifications

12+ years across supply chain operations, data products and analytics or AI, including 3–5 years managing teams.
Hands-on knowledge of at least one area: demand/supply planning, materials, inventory optimization, procurement or logistics.
Experience with data products, data governance and quality monitoring.
Experience building semantic layers or self-service analytics platforms.
Working knowledge of a modern data stack (for example Snowflake, BigQuery or Databricks, dbt, Airflow).
Understanding of the ML lifecycle and GenAI concepts (LLMs, RAG, agents).
Strong SQL and data modeling.
Experience in a global, matrixed organization.
Bachelor’s Degree in Computer Science, Engineering, or a related field.