Amazon’s Last-Mile Business Intelligence team’s (LMAQ-BI) mission is to build optimum business solutions to gain maximum efficiency in last-mile operations of Amazon logistics. Amazon runs one of the most dynamic e-commerce marketplaces in the world, with nearly 2 million sellers worldwide selling hundreds of millions of items in ten countries. Amazon logistics is one of the promising logistic partners to support this scale of Amazon’s business. As such, LMBI designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon last mile operations. The LMAQ-BI organization is looking for a Business Intelligence Engineer. The team provides insights about operations and analytical solutions to help drive risk pattern recognition, uncover trends, build analytical frameworks, and support customer experience in logistics.
As a Business Intelligence Engineer, you will be responsible for modelling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, & visualization techniques and maintaining requisite dashboards
You will need to collaborate effectively with business and product leaders across Planning teams, Operations teams, OR scientists and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and analytical techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner.
• Use predictive analytics and data mining to solve complex problems and drive business decisions
• Employ the appropriate algorithms to discover patterns of risks, efficiency improvement, and help improve cost-savings in last-mile logistics.
• Design experiments, test hypotheses, and build actionable models to optimize last-mile business processes
• Adept at translating business needs into technical requirements and translating data into actionable insight
• Solve analytical problems, and effectively communicate methodologies and results
• Draw relevant inferences and insights from data including, identification of trends and anomalies
• Work closely with internal stakeholders such as business teams, product managers, engineering teams, and partner teams