Amazon is looking for a highly analytical Engineer to join the CA Supply Chain Team. The Canada Supply Chain team is responsible for the long-term capacity and network architecture planning, as well as the short-term supply chain execution between Amazon’s sellers/vendors, fulfillment centers and downstream partners. This role will support planning, execution, optimization and continuous improvement in the supply chain consisting of hybrid Fulfillment Centers and dedicated cross dock buildings in future. The ability to diagnose problems and to conceive-build-implement solutions will be key to success.

As a Business Intelligence Engineer, you will generate insights that will guide operational excellence and strategy for our customers. analysis is at the core Amazon’s culture, and your work will have a direct impact on decision-making and strategy for our organization. You will be gathering operational insights, run statistical analysis, mining making recommendations, and helping senior leaders make key decisions. You will have the opportunity to work with large and diverse data sets to gather insights from across, using AWS Infrastructure.
The ideal candidates will have excellent analytical and statistical abilities, acumen and judgment, intense curiosity, strong technical skills, and written and verbal communication skills. They will have a strong bias toward driven decision-making. They will be a self-starter, comfortable with ambiguity, able to think and be creative (while paying careful attention to detail). They will enjoy working in a fast-paced dynamic environment. If you are excited about it, are results oriented, and want to join a growing analytics team within Amazon, this role is for you.
Are you up for the challenge?

Key job responsibilities
- Design, develop and maintain scaled, automated, user-friendly systems, statistical analysis and prediction, reports, dashboards, etc. that will support the needs of the .
- Apply deep analytic and skills to extract meaningful insights and learning from large and complicated sets using the appropriate statistical forecasting model and Machine Learning models.
- Be hands-on with ETL to build pipeline to support automated reporting.
- Serve as liaison between the planning and technical teams to achieve the goal of providing actionable insights into current performance, ad hoc investigations to support future innovations and continuous improvements. This will require gathering and manipulation, problem solving, and communication of insights and recommendations.
- Build various rich visualizations to tell the story of trends, patterns, and outliers.
- Recognize and adopt best practices in reporting and analysis: integrity, test design, analysis, validation, and documentation.