Apple Online Store - Senior Web Analyst
Posted: Aug 19, 2019
Weekly Hours: 40
Role Number: 114201119
The people here at Apple don't just build products - we craft the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that supports 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. As a web analytics authority, you are deeply involved with the infinitely valuable data generated by a major website. You flourish with actively finding opportunities to improve every online customer's visit experience. You have the analytics skill to tease groundbreaking insights out of the online signals and the communications skills to deliver your compelling message to a wide variety of audiences: senior management, product management, marketing, finance, and others. What better way to demonstrate the value of your skills and experience into a more valuable career opportunity than as the Senior Web Analyst for the Apple Online Store! Ours is a leading eCommerce environment like no other, representing the most admired brand in over 40 countries worldwide. With multi-platform web implementations and an elite shopping app, AOS is a powerful presence, providing a unique opportunity for an imaginative and motivated Web Analyst to light the way for the Apple Online Store business team while enjoying a scale and scope of personal growth available only at Apple.
- 5 years web analytics and reporting experience in an Omniture/Adobe data capture system.
- 3+ years with an online business built on consumer retail products. 2+ years of experience developing or working with tracking systems for online behavior.
- Business insight and leadership skills
- Advanced expertise in the generation, collection and analysis of visitor behavior data.
- Demonstrated ability to extract, conceptualize and communicate the significant patterns of visitor behavior from web data that identifies meaningful business opportunities.
- Confirmed ability to deliver clear and actionable data in person and through reporting tools.
- Shown ability to define, lead and complete complex inter-departmental projects.
- Advanced command of data visualization techniques.
- Documented ability to work effectively with technical partners.
- Experienced and confident presenting findings verbally to management at any level.
- Expert knowledge of web tools and resources, data analytics technologies such as SQL, SAS, R, etc.
- Expert knowledge of and experience using Adobe Workspace, Adobe Workbench
- Expert experience in information delivery technologies, especially Tableau, Excel, Keynote.
- In-depth knowledge of shell-scripting technologies like Python, PHP, Bash, VBA, etc.
- Significant experience working with large data resources in Teradata.
- Experience with data mining and modeling tools in SAS, R etc. Application scripting experience including integrating API interfaces.
Develop and maintain working relationships with a core group of business partners needing deep understanding of the website functionality and visitor experience. Provide intellectual and interpretive leadership on the meaning of data generated by the Apple Online Store as implemented in a multiplicity of electronic environments. Work closely with the web data infrastructure teams on the definition and implementation of new information to insure comprehensive coverage and descriptive precision. Provide analytics and interpretive mentorship on traffic sources and conversion value as well as the effectiveness of product discovery, selection and purchase experience. Provide analytics and interpretive mentorship on use of the Apple Online Store app, both as an online purchasing resource and as an in-store shopping support tool. Insure the consistency and availability of web analytics across all countries in which the Apple Online Store does business.
Education & Experience
Required: BS in mathematics, statistics, econometrics, computer science or other quantitative discipline. Strongly preferred: MS in statistical methods, machine learning, computer science or econometrics
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