Role Overview
This is a highly visible role that requires collaboration across teams and integration of technical and operational knowledge to achieve objectives. The position involves interacting with teams across regions and functions, networking across Apple's organization, and driving data science and process improvement initiatives.
Key Responsibilities
* Deep dive into operational data to assess program performance, identify trends, and opportunities for improvement.
* Identify and evaluate operational risks, implementing contingency plans to mitigate them.
* Lead data science and process improvement initiatives with a focus on identifying and implementing data-driven solutions to enhance efficiency, performance, and scalability in the EMEIA region and global operations.
* Drive AI, automation, and optimization solutions for operational challenges using technical tools to improve processes and outcomes.
Requirements
* Evaluate and interpret large data sets, analyse, and present data with significant insights and actionable recommendations to peers and leadership for impactful business decisions.
* Partner with subject matter experts, data science, and BI team to deliver a roadmap of initiatives for Shared Services.
* Champion transformative changes that will result in future-proofed and scalable solutions to support Apple's continued growth.
* Strong understanding of how to leverage AI, machine learning, and automation techniques to tackle complex operational and business problems that drive important improvements & efficiencies across all regions.
* Bachelor's degree in Data Science and Analytics, Computer Science, or related field.
* Proficient in coding with SQL and Python, capable of writing complex queries, automating processes, and developing data models.
Desirable Qualifications
* Confidence to make critical decisions and deliver results under tight timelines, with flexibility to adapt to the challenges of a fast-paced environment.
* Possession of passion for enhancing the customer experience.
* Experience and proficiency with cloud-based databases such as Snowflake.