The difference between data and intelligence is context. This role enriches data with business context to produce insights that enable intelligent decisions. Join Apple's Information Systems and Technology (IS&T) organization, the engine powering Apple. As a member of the Employee Productivity & Support Data Science team, you will use data to improve how Apple trains its employees and delivers knowledge resources. You will pull and prepare data from multiple systems, build dashboards and visualizations, and conduct analyses that help learning and development leaders understand program effectiveness and make informed decisions. This role is about interpreting data, extracting insights, and partnering closely with the business to turn those insights into better decisions. In this role, you will support IS&T's Knowledge & Training group by building and maintaining the analytical assets it relies on — dashboards, reports, and ad-hoc analyses that surface how training programs and knowledge resources are performing across the organization. You will draw on your expertise in learning and development analytics to understand how employees engage with training content, identify where programs can improve, and develop metrics that measure effectiveness beyond attendance. A core part of the role is partnership: you will work directly with knowledge and training leaders to understand their challenges, translate them into analytical work, and deliver findings that are clear, accurate, and actionable. You are not building in isolation — you are a thought partner who understands the business well enough to know what to measure and why it matters. Day to day, you will write SQL to model data from large datasets, build and maintain Tableau dashboards, conduct analyses to identify trends and anomalies, and present your findings to stakeholders at various levels — all while using AI tools to accelerate your analytical work. The ideal candidate is someone who is technically strong, detail-oriented, and equally motivated by the work the data enables as by the data itself.
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Job Type
Full-time
Career Level
Mid Level