Business Intel Engineer II, ROW Sharp Team
Amazon.com
Amazon's ROW central team is established with the mission to drive customer experience and cost improvement and support business growth in the countries in scope. ROW central team covers IN, JP and Emerging Countries (BR, MX, MENA, SG, AU). The UPx and Placement BI team build up and monitor critical metrics across supply chain flow, and conducts advanced data analysis to identify system algorithm improvement opportunities. This team has worked with both local business team and multiple SCOT teams for years to bring data visibility, automate data solutions with key focus on fulfillment experience optimization, inventory placement, S&OP planning and inbound/removal etc. The BI role will be a dedicate resource for emerging countries to support the requests along with network expansion and volume increase in coming years.
Key job responsibilities
ROW SC BI team is looking for a customer-focused, detail-oriented, self-motivated, hands-on BIE. He/she would work closely with all emerging countries on:
1) Metrics build-up/maintenance across all supply chain functions, including but not limited to key metrics on UPB, UPPD, instock rate, transfer volume etc.
2) Translating business questions and concerns into specific analytical questions that can be answered with available data using Statistical methods.
3) Simulations and modeling with internal or external tools to study complex supply chain use cases on inventory placement and order fulfillment
4) Metrics related deep dive, call-outs on weekly and monthly basis.
Key job responsibilities
ROW SC BI team is looking for a customer-focused, detail-oriented, self-motivated, hands-on BIE. He/she would work closely with all emerging countries on:
1) Metrics build-up/maintenance across all supply chain functions, including but not limited to key metrics on UPB, UPPD, instock rate, transfer volume etc.
2) Translating business questions and concerns into specific analytical questions that can be answered with available data using Statistical methods.
3) Simulations and modeling with internal or external tools to study complex supply chain use cases on inventory placement and order fulfillment
4) Metrics related deep dive, call-outs on weekly and monthly basis.
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