At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We are looking for a Business Intelligence Engineer to be a part of the Grocery Analytics team who will build models and algorithms for procurement, selection, and pricing tools.
This role is both creative and data driven - we need someone who can review our current infrastructure, isolate improvement opportunities, help us think big about what to consider in terms of localization, scalability, commodity management, and long term automation. This role will report into the global Grocery Analytics Team leader and is an individual contributor role.
We are looking for someone who will scope and execute analyses to formulate conclusions and recommendations to be presented to senior leadership on business growth opportunities. You will also be responsible for producing insights that will help shape effective strategies to better meet our customers' needs. You will work closely with internal teams, and partners across the grocery business line and other partner teams in these areas to provide decision support in this rapidly evolving space.
This role requires an individual with excellent statistical and analytical abilities, deep knowledge of business intelligence solutions, and have the ability to work with technology, product development, and business teams. The successful candidate will have passion for data and analytics, be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and entrepreneurial environment, and driven by a desire to innovate Amazon's approach to this space.
Develop new and innovative analyses to inform product strategy and design. This analysis will determine approach and roadmap for key strategic initiatives.
Analyze relevant business information, and uncover trends and correlations to develop insights that can materially improve our product and strategy decisions.
Develop clear communications for recommended actions.
Establish new, scalable, efficient, automated processes for tracking and reporting on progress of initiatives.
Use machine learning, data mining and statistical techniques to create new, scalable solutions for business problems.