Do you want to play a crucial role in the future of Amazon's retail business by applying advanced analytical techniques at the largest scale possible?
The Fulfillment Optimization (FO) team is responsible to develop and support technologies that enable the optimal use of Amazon and subsidiary transportation, operations, and delivery networks. We believe that through investment in new transportation, operations, and delivery technologies, we will consistently improve internal and external customer experience, and increase confidence and trust in Amazon as the single, best option to get what you want when you want it. We are part of the Supply Chain Optimization Technology (SCOT) that develops and manages systems that optimize inventory acquisition and placement so products are available for fast delivery. Our systems also optimize transportation and fulfillment plans to enable delivery options for our customers.
FO is seeking an exemplary Business Intelligence Engineer with broad technical skills to build analytic and reporting capabilities that enable optimization of our fulfillment plans for our millions of customers worldwide. The ideal candidate is a highly analytical, critical thinker with advanced problem solving, data mining, and software development skills. They will enjoy working with world-class economists, research scientists, data engineers, and software developers to drive decisions across Amazon's retail and operations teams. Successful members of this team are customer obsessed, flexible, and collaborative team players who enjoying working across functions and organizations to solve problems and get results. They ask hard questions and build scalable solutions that provide critical business insight necessary to influence decision making across retail and operations teams. They find timely answers buried in large data sets and complex systems, identify root causes, get their hands dirty building data systems and sharing insight.
• Defining, developing and maintaining critical business and operational reports reviewed on a weekly, monthly, quarterly, and annual basis
• Analysis of historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations
• Collaborating with software development teams to implement analytics systems and data structures to support large-scale data analysis and delivery of machine learning and econometric models
• Mining and manipulating data from database tables, simulation results and log files
• Identifying data needs and driving data quality improvement projects
• Understanding the broad range of Amazon's data resources, which to use, how, and when
• Thought leadership on data mining and analysis
Watch this video to learn more about our organization: http://bit.ly/amazon-scot
Amazon is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
• BA/BS degree in computer science engineering, economics, statistics, mathematics, econometrics, or a similar quantitative field
• 5+ years work experience in data mining and analysis
• Proven analytical and quantitative skills
• SQL expert with prior success working with extremely large data sets
• Working familiarity with industry standard data analysis and presentation tools
• Prior experience in design and execution of analytics projects
• Demonstrated ability to directly partner with business owners to understand requirements
• Demonstrated ability to work with technical teams to deliver accurate and scalable reporting and analytics solutions
• Effective spoken and written communication to senior audiences, including strong data presentation and visualization skills
• Detail-oriented with an aptitude for solving unstructured problems
• MS degree or higher in computer science engineering, statistics, mathematics, econometrics, or a similar quantitative field
• Experience with web development/automation, scripting languages, and functional programming
• Proficiency in statistical software such as R, S-plus, SAS, STATA
• Experience applying machine learning, statistical modeling or related analytic techniques
• Experience with Supply Chain and Operations