Apple

Compensation

Full Description

The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Apple’s Sales organization generates the revenue needed to fuel our ongoing development of products and services. This in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers. The WW Channel Strategy & Operations (CSO) team focuses on developing and deploying worldwide sales programs and standard methodologies to deliver best customer experience in the Channel, and drive Apple Channel sales. With deep functional expertise in digital, physical and people enablement spaces, WW CSO closely collaborates with many cross-functional teams at both worldwide and regional levels. We are looking for a data scientist to create, design and implement solutions that best leverage CSO’s store experience and performance data to create analytic solutions that will drive decision-making across the WW CSO organization. DESCRIPTION We are seeking a technical practitioner who combines data engineering depth with data science and analytical problem-solving to enable high-quality, scalable data capabilities that drive decision intelligence across our organization. MINIMUM QUALIFICATIONS 7+ years of experience in Data Engineering, Data Science, Applied Analytics, or similar hybrid roles Proven ability to design and optimize data pipelines and datasets for analytics and ML use cases Strong proficiency in Python and SQL, with experience in distributed processing frameworks (e.g., Spark / Databricks) Experience working with large cross-functional data ecosystems, including data collection, instrumentation, and quality standards Ability to monitor, assess, and improve data quality, including anomaly detection, data validation, and lineage Demonstrated ability to synthesize needs across data science, BI, engineering, and product partners into cohesive data strategies PREFERRED QUALIFICATIONS Strong communication skills — able to adjust messaging for technical and non-technical audiences Highly collaborative and grounded, invested in collective outcomes rather than individual credit Master’s degree in Data Science, Computer Science, Engineering, Information Systems, or equivalent practical experience