Project Description

Data Scientist / Statistician / Economist

Santa Clara Valley (Cupertino), California, United States

Summary

Posted: Nov 22, 2018
Weekly Hours: 40
Role Number: 114086584
At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. If you bring passion and dedication to your job and there’s no telling what you could accomplish. This is a visible and important role at Apple and will have global impact across all of Apple’s Internet Services. The individual in this role will be responsible for interpreting quantitative data and developing statistical models to forecast and monitor infrastructure demand for iCloud and other Apple services.

Key Qualifications

  • Strong background in statistics or econometrics: regression analysis, causal inference, time series analysis, GLM, logistic regression, probability theory, regularization, interest in machine learning algorithms
  • Work with various engineering teams to understand current and future infrastructure demand (storage, network, CPU, etc.)
  • Build models to forecast the financial impact of new hardware and software releases across different scenarios
  • Develop internal visualization and modeling tools to facilitate data-driven decisions
  • Present results and other analytical findings to business partners
  • 2+ years of experience in time series analysis, forecasting, and data analysis
  • Strong statistical background and experience with time series modeling (e.g. ARIMA, exponential smoothing, time series regression methods etc.)
  • Experienced R programmer also proficient in other languages important to the ETL data pipeline (e.g. SQL)
  • Experience with data visualization packages (e.g. ggplot2, plotly) and advancing multiple projects at once on a tight schedule
  • Excellent collaborator with strong written and verbal communication skills
  • Ability to share results with a non-technical audience
  • Innate curiosity
  • Experience in modeling (e.g. bayesian structural time series, dynamic linear models)
  • Experience with Stan, Stan interfaces (e.g. brms, rstanarm)
  • Experience building and maintaining R packages
  • Advocate and practitioner of version control and reproducible code

Description

Work with various engineering teams to understand current and future infrastructure demand (storage, network, CPU, etc.) Build models to forecast the financial impact of new hardware and software releases across different scenarios Develop internal visualization and modeling tools to facilitate data-driven decisionsPresent results and other analytical findings to business partners

Education & Experience

Minimum Bachelor’s degree in Statistics, Mathematics, Economics, or other quantitative disciplines. Masters or PhD preferred