- Cupertino, CA
Posted: Feb 12, 2020
Weekly Hours: 40
Role Number: 200145057
We're a diverse collective of thinkers and doers, continuously reimagining our products and practices to help people do what they love in new ways. That innovation is inspired by a shared commitment to great work - and to each other. Because learning from the people here means we're learning from the best. Do you have a strong passion for data and effective visualization techniques? As a Data Scientist on the Retail Analytics team, you play an integral role in helping Apple Retail make decisions using data. Design, refine, and create innovative analyses and data products. Leverage large and complex data sources, deriving actionable insights, delivering dynamic and intuitive decision tools, and presenting your findings to key executives.
- 2+ years of related work experience in consulting or other related business facing role
- Fluency in SQL for data access, manipulation, and validation
- Proficiency in either R, Python or SAS for data analysis
- Passion for data visualization and information design (proficiency in Tableau preferred)
- Capable of clearly communicating complex analyses to a non-technical audience, including extensive experience presenting to leadership groups
- Ability to initiate, refine, and complete projects with minimal guidance
You will partner with cross-functional teams to identify, frame, prioritize, and answer business questions where analytics can be most impactful. Design and implement analytics and reporting tools to support key decisions on a wide variety of topics including product launches, customer experience, and operational performance. Quickly outline and build customized analyses for Retail leadership and perform all aspects of analysis including data acquisition and manipulation, programming, data visualization, documentation, and presentation of results. Develop a deep understanding of our retail customer base and purchase choices and contribute to the development of tools to improve team efficiency and productivity.
Education & Experience
Minimum of bachelor's degree, preferably in related quantitative field
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