Applied Economist / Statistician

Starbucks
Seattle - United States
S: Competitive

Starbucks economists apply economic thinking to location analytics, forecasting, program evaluation and other areas. You will build econometric models, using multiple data sources, and apply economic theory to solve business problems in a fast-moving environment.

Economists at Starbucks are expected to develop new techniques to process large data sets, address quantitative problems, and contribute to the design of automated systems around the company.

Key Responsibilities:
Design, develop and deploy data-driven predictive models/algorithms to solve business problems using the latest technologies in Operations Research, Machine Learning and Statistical Modeling
Design, build and operationalize statistical and econometric models
Perform model maintenance and update analyses as needed
Assist in the design and delivery of automated, scaleable analytical models to stakeholders
Work collaboratively with economists and data scientists to assist in the design and implementation of analysis to answer challenging business questions
Closely work with Starbucks Technology teams to build scaleable, efficient systems from prototype to production
Aggregate and analyze data pulled from disparate sources and related industry and external benchmarks; provide insights and a point of view on analysis and recommendations
Report results in a manner which is both statistically rigorous and relevant to all audiences

Basic Qualifications
Masters (Ph.D. preferred) in economics or highly related field
Work experience in applied statistics or econometrics
Experience working in multiple types of database environments (Oracle, MS SQL, etc.)
Experience in using R or Python is required
Deep understanding of statistical theories and their application to solve complex problems

Preferred Qualifications
Deep knowledge of statistical and machine learning algorithms such as regression, decision trees, neural networks, clustering, collaborative filtering, survival analysis, etc.

Job summary