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Senior Business Intelligence Engineer - Advertising, New York, New York

CategoryBusiness Intelligence
Job typeFull Time
CountryUnited States of America
StateNew York
CityNew York
What is Amazon's Advertising business like?
Amazon is investing heavily in building a world-class Advertising business where we run relevant display ads on key locations across our Retail website, Retail Mobile Shopping Apps, Devices, Third Party websites, Third Party Mobile Apps and Physical Stores. The goal of our Advertising program is to drive brand awareness, product discovery and product sales both online, offline and physical store channels.

What is your team responsible for?
Our team is responsible for full-stack implementation and integration of new advertising products, which power the ad content, targeting, and attribution across our advertising network with physical stores. This is an opportunity to get in on the ground floor and help shape our advertising technologies, products and business. Our products include web tools (used by marketing managers - both internal and external) and web services (used by developers within advertising) to implement unique experiences for physical store shoppers and advertisers .

If I were hired, what would I be working on?
In this role you will have ownership and responsibility to analyze physical store shopping data in order to propose innovative and profitable business initiatives to senior management/executives. You will collaborate with the product and engineering teams to find and create ways to measure the shopper experience to drive business outcomes. This is a large initiative that spans across multiple existing and to be formed engineering and product teams within the Advertising organization.

In this role you will:
• Apply data mining and quantitative analysis to understand how our customers interact with us and identify the best way to improve the customer experience and meet our goals
• Own the design, development, and maintenance of ongoing performance metrics, reports, analyses, dashboards, etc. to drive key business decisions
• Build scalable solutions / self-serve platforms that will provide data / KPIs to inform business decision making
• Build various data visualizations to tell the story and let the data speak for itself
• Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
• Proactively developing new metrics and studies to quantify customer behavior.
Why should I join your team?
Are you interested in building a green field product opportunity within Amazon Advertising? Do you want to have direct and immediate impact on millions of customers every day? If you are a self-starter, curious to identify patterns in data and how they relate to the business outcomes, and are intrigued by ambiguous problems, this is a unique and rare opportunity to build a new initiative from scratch with some of the best full-stack engineers and product managers. We pioneer the usage of modern full-stack technologies at Amazon scale. Join today and you will transform how customers discover and shop at physical stores!

Basic Qualifications:
• 5+ years of relevant work experience in a role requiring application of analytic skills to integrate data into operational/business planning
• Proficiency with SQL, ETL, data warehousing, Tableau and other common analytical tools
• Demonstrated ability to draw insights from data and clearly communicate them to both business and technical teams
• Be self-driven, and show ability to deliver on ambiguous projects with limited data
• Demonstrated ability to influence across a large, multi-faceted organization

Preferred Qualifications:
• Advanced degree in Computer Science, Mathematics, Statistics, Economics, or other quantitative field
• Experience using cloud data repository services such as AWS Redshift, S3
• Experience with Python, R or other statistical/machine learning software
• Experience working in very large data warehouse environments
• Understanding of machine learning algorithms such as Linear Regression, Logistic Regression, Time Series forecasting, etc.
• Strong project management skills to coordinate projects across cross-functional teams, including business intelligence, engineering, marketing, product management, and finance.
• Experience in consumer-facing industry


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