Data Scientist / Statistician / Economist

Apple
Cupertino - United States
S: Competitive

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 bayesian statistics and 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

Job summary