Data Scientist - Strategist - Apple Retail

Santa Clara Valley (Cupertino), California, United States
Operations and Supply Chain

Summary

Posted: Nov 8, 2018
Weekly Hours: 40
Role Number: 113628769
The Apple Retail Data Sciences team provides insights through data analytics and predictive modeling. We are looking for an expert Data Scientist to partner closely with the business to drive strategic decisions.. You will be excellent at integrating data sources, building applied regression models, deriving valuable insights and communicating meaningful findings and insights.

Key Qualifications

  • 5+ years of revenue forecasting experience needed, preferably within a retailing domain
  • Excellent statistical skills in applied regression, spatial and time series modeling
  • Deep understanding of design of experiments principles
  • Proven working knowledge of SQL
  • Proven working knowledge of SAS and R
  • Experience with scripting and automation of data extraction, transformation and modeling outputs
  • Experience with Data Visualization such as Tableau
  • 2 or more years meaningful experienced in GIS preferred

Description

Be a self-starter, motivated, accountable, and a highly upbeat teammate Excellent communication skill with the ability to distill complex methodologies and findings into simple and actionable insights Can craft modeling frameworks to assess and estimate impact of new store openings and channel cannibalization on revenue and customer experience

Education & Experience

Master’s Degree in Statistics, GIS, Applied Economics, or related disciplines with 5 or more of meaningful work experience. Bachelor’s Degree considered with at least 7+ years of relevant work experience

Additional Requirements

  • Apple is an Equal Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities. Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants.