Global Mile Expansion Team
At Global Mile Expansion team, our vision is to become the carrier of choice for all of our Selling Partners' cross-border shipping needs, offering a complete set of end-to-end cross-border solutions from key manufacturing hubs to footprint countries supporting businesses that use Amazon to grow globally. As we expand, the need for comprehensive business insight and robust demand forecasting to aid decision-making on asset utilization, especially where we know demand will be variable, becomes vital, as well as operational excellence. We are building business models involving large amounts of data and macroeconomic inputs to produce robust forecasts that help enhance operational excellence and continue improving the customer experience. We are looking for an experienced economist who can apply innovative modeling techniques to real-world problems and convert them into highly business-impacting solutions. Key Job Responsibilities
Experienced in using mathematical and statistical approaches to create new, scalable solutions for business problems. Analyze and extract relevant information from business data to help automate and optimize key processes. Design, develop, and evaluate highly innovative models for predictive learning. Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation. Research and implement statistical approaches to understand the business's long-term and short-term trends and support strategic planning. BASIC QUALIFICATIONS
Industry, consulting, government, or academic research experience. Design and use of business case models. PREFERRED QUALIFICATIONS
Deep knowledge in time series econometrics, asset pricing, empirical macroeconomics, or the use of micro and panel data to improve and validate traditional aggregative models. Degree in mathematics, economics, applied science, engineering, or equivalent. Background in statistics methodology, applications to business problems, and/or big data. Research track record. Effective verbal and written communication skills with both economists and non-economist audiences. Experience in developing and executing an analytic vision to solve business-relevant problems.
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At Global Mile Expansion team, our vision is to become the carrier of choice for all of our Selling Partners' cross-border shipping needs, offering a complete set of end-to-end cross-border solutions from key manufacturing hubs to footprint countries supporting businesses that use Amazon to grow globally. As we expand, the need for comprehensive business insight and robust demand forecasting to aid decision-making on asset utilization, especially where we know demand will be variable, becomes vital, as well as operational excellence. We are building business models involving large amounts of data and macroeconomic inputs to produce robust forecasts that help enhance operational excellence and continue improving the customer experience. We are looking for an experienced economist who can apply innovative modeling techniques to real-world problems and convert them into highly business-impacting solutions. Key Job Responsibilities
Experienced in using mathematical and statistical approaches to create new, scalable solutions for business problems. Analyze and extract relevant information from business data to help automate and optimize key processes. Design, develop, and evaluate highly innovative models for predictive learning. Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation. Research and implement statistical approaches to understand the business's long-term and short-term trends and support strategic planning. BASIC QUALIFICATIONS
Industry, consulting, government, or academic research experience. Design and use of business case models. PREFERRED QUALIFICATIONS
Deep knowledge in time series econometrics, asset pricing, empirical macroeconomics, or the use of micro and panel data to improve and validate traditional aggregative models. Degree in mathematics, economics, applied science, engineering, or equivalent. Background in statistics methodology, applications to business problems, and/or big data. Research track record. Effective verbal and written communication skills with both economists and non-economist audiences. Experience in developing and executing an analytic vision to solve business-relevant problems.
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