Amazon

Business Intelligence Engineer III, Emerging Marketplaces Analytics

Job Description

Emerging Marketplaces Analytics team builds Analytics solutions that drive customer growth across all EMs for Amazon. These solutions include building and scaling complex analytical frameworks, mining data-driven insights through comprehensive dashboards, using ML/AI to address business problems, and leading Analytics for key strategic review meetings with leadership.

Key job responsibilities
Key job responsibilities
- Conduct deep dive analyses of business problem statements and formulate conclusions and recommendations to leadership
- Share written recommendations and insights for key stakeholders that will help shape organizational strategic decisions and priorities
- Contribute to the design, implementation, and delivery of BI solutions for complex and ambiguous problems
- Simplify and automate reporting, audits and other data-driven activities
- Partner with other BIEs to enhance data infrastructure, data availability, and broad access to customer insights
- Develop and drive best practices in data integrity, consistency, analysis, validations, and documentation
- Learn new technology and techniques to meaningfully support internal stakeholders and process innovation

About the team
We are the Emerging Prime, Lifecycle and XCM (PLX) EMXO team that builds & orchestrates inputs towards Customer Growth and Engagement for our Stores across ten locales. We do this through: (i) Crafting EM-specific frameworks where none exist to guide inputs, prioritization and investment decisions; (ii) Building foundational tech, tools & capabilities to enable inputs at scale, sharper targeting of key customer cohorts, driving down Cost-To-Serve (CTS) through core builds; and (iii) Orchestrating EM-focused builds by influencing partner WW teams and x-EM experiments across the customer Lifecycle - 8+ years of professional or military experience
- 6+ 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 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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