Amazon Sr BIE Amazon Pay Marketing 

United States, Washington, Seattle 

690352218

Key job responsibilities
• Work at both the strategic and tactical levels to evolve our marketing analytics strategy
• Roll up sleeves to develop and implement marketing data pipelines, metrics, reports and dashboards that support the organization's strategic priorities
• Establish scalable, efficient, automated processes for tracking and reporting on progress of marketing initiatives
• Accelerate Gen AI initiatives roll out for marketing use cases
• Partner with Marketing Managers to build new models for marketing segmentations and customer journey, marketing attribution and incrementality that will drive our marketing strategy, prioritization and budget allocation
• Partner with Central Analytics, Software engineering and Data Engineering teams to build and/or integrate Amazon Pay data infrastructure solutions for marketing-specific needsA day in the life
• Work directly with marketing customers to understand their strategy and needs, brainstorm solutions and create project plans
• Extract and QA marketing data, automate processes for recurrent data reporting and analysis
• Size and prioritize data requests from marketing organization, and manage them within own roadmap of strategic priorities
• Participate and support business reviews, annual planning and goal setting exercises
• Adopt best practices in reporting and analysis for marketing analytics: data integrity, test design, analysis, validation, and documentation
• Collaborate directly with Central Analytics and Engineering teams

- 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