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 team leverages advanced data mining techniques and deep knowledge of TQ to disambiguate genuine IVT from false positives in the absence of ground truth. The team must efficiently balance producing bias-for-action insights while navigating through vast amounts of data (billions of records) and building high standard systems that scale for customised program/supply specific use-cases.
As a Sr. Business Intelligence Engineer (BIE) for TQ Analytics, you will play a thought leadership role in defining interventions that help achieve business objectives. You will lead the BI efforts for the team and consistently produce exceptional analytical deliverables and high quality results. You are the custodian of the team’s program metrics and work continuously to up-level the interpretability of metrics by developing robust, scalable analytical solutions. 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 statistical models that detect and filter IVT.
Key job 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.
- 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
- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing, analyzing and communicating results to senior leadership
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