Job summaryAmazon Web Services (AWS) is obsessed with ensuring the success of our customers. To this end, we want to better understand each type of customer we have and at what point in their Cloud journey they'd benefit from the different types of help AWS can provide. For whom is temporary credit more helpful than a discount? What are the returns to salesperson effort for a mature vs. a new AWS customer? What other customer features tell us that it's time to reach out and build a relationship?We're looking for someone with a background in program/policy evaluation. ML skills are a huge plus here, as you'll be working to find new patterns/clusters in large datasets.Basic Qualification· PhD in Economics or a related field· Three years of work experience in the private sector· Strong proficiency in at least one of the following statistical software packages: Python, R, Stata, or MatlabPreferred Qualifications· Strong background in econometrics (e.g., forecasting, time series, panel data, program evaluation, and/or high dimensional problems), probability and statistics, economic theory, and quantitative methods· Strong empirical research track record in applied macroeconomics, econometrics, finance, labor economics, public economics, industrial organization, or a related field· Proven experience with the design and development of machine learning solutionsDemonstrated ability to design solutions to real world business questions.· Strong verbal and written communication skills (e.g., ability to write and present narratives to different levels of leadership).Ability to work in a very fast-paced business environment· Experience with programming languages such as Python, Java, C++, Ruby, and /or Big Data processing platforms such Hadoop, Map Reduce, Spark is a plus.· Ability to work in a fast-paced business environment· Experience with Enterprise Sales data (e.g., SFDC)Job Locations: Seattle, WA, Dallas, TX, Boston, MA, Arlington, VAKey job responsibilitiesFind heterogeneous treatment effects to help the business prioritize interventions, use large and small sample methods for causal inference.About the teamWe're a team of economists, engineers, data scientists and research scientists who are responsible for using data to help maximize the productivity of the thousands of AWS sales reps working to grow the business. We mostly build prototypes and write white papers, but as our products become successful and adopted we move them to production as well.