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Amazon
AOP team powers the Data and Insights for ROW (Rest of World) Fulfillment Operations. Team is responsible for development of large-scale and business-critical BI and analytics solutions for Operations.
AOP team broadly works in three areas: a) Build data products to enable Operations decision making and improve Operations performance. Data products encompass BI/Reporting solutions including development of automated and self-service reports/dashboards and publishing of business-critical decks (xBR, Peak, Contingency) as well as Analytics solutions including development of tools and defect attribution bridges; b) Build science artefacts in realm of forecasting, fraud detection, work productivity improvements and other areas to drive Ops performance; c) Drive analytics-led continuous improvements programs in realm of Ops defect reduction and Cost-savings.
This role within AOP would directly work with AOP-leader to: a) Build cross-mile capabilities for ROW marketplaces; b) Set-up and drive adoption of BI Engineering best practices across AOP; c) Develop prototypes as well as launch full-scale solutions incorporating GenAI techniques; d) Build scalable ways to mine business-leading insights at scale for ROW operations. This role is a hands-on role requiring a person to be adept with both existing and new age technologies in data space. This role is flexible to work on all three areas enlisted in AOP scope.
About the team
AOP team powers the Data and Insights for ROW (Rest of World) Fulfillment Operations. Team is responsible for development of large-scale and business-critical BI and analytics solutions for Operations. We are team having all scope complexity for all Data job families giving you an unique opportunity to explore different roles while solving high-impact Operations problems. - 10+ years of professional or military experience
- 5+ years of SQL experience
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience with theory and practice of design of experiments and statistical analysis of results
- Experience with AWS technologies
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with theory and practice of information retrieval, data science, machine learning and data mining
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