Advertising at Amazon is a fast-growing, multi-billion dollar business. It spans desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third-party publishers; and extends across the US, EU, APAC, and an increasing number of international geographies.
The Supply Quality (SQ) group operates across all Amazon Advertising products to provide invalid traffic (IVT) filtration, viewability prediction and measurement, and content adjacency policy enforcement capabilities. Within SQ, Traffic Quality (TQ) concerns itself with the validity of ad traffic i.e. if the ad event (bid, impression or click) is generated from a human user or bot (invalid) and the TQ Analytics team focuses on building key metrics and reporting, root cause analysis and critical stakeholder communications on changing trends and patterns for this area. The TQ Analytics team also focuses on building heuristic based models and techniques to address IVT and ad fraud.
As a Business Intelligence Engineer (BIE) for TQ Analytics, you will play a thought leadership role in defining interventions that help achieve business objectives. You are right, a lot. You are independent, able to work on multiple related projects and always on the lookout to optimize the information flow process. You will collaborate with Scientists and Engineers to analyze trends and analyse statistical models that detect and filter IVT.
Key job responsibilities
Responsibilities
* Design, implement and support a scalable and reliable information model for storing, processing, analyzing and reporting on data across Amazon properties and partners.
* Define and implement data quality guardrails and monitoring mechanisms as the custodian of data quality
* Compose and present measurable and actionable insights into complex business problems to senior leadership.
* Automate with every iteration to enable self service by others on the team and to continuously expand on your ability to dive deep.
* Perform exploratory data analysis and apply statistical techniques to help Scientists build models that detect and filter IVT.
* Define and implement metrics that continuously evaluate models.
* Understand a broad range of Amazon’s data resources and know how, when, and which to use and which not to use.
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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