Data Engineer, Ads Science Analysis & Tech (ASAT)

About the role

The Ads Science Product Team's Mission: Work alongside those who need product data to apply objective perspective and business logic to uncover insights, advise strategic decisions, and adjust to industry changes.

Requirements

• 1+ years of data engineering experience
• Experience with SQL
• Experience with data modeling, warehousing and building ETL pipelines
• Bachelor's degree
• Experience using AI to automate and build with github (other sources) to showcase projects.
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
• USA, CA, Palo Alto - 116,500.00 - 185,000.00 USD annually
• USA, NY, New York - 111,400.00 - 185,000.00 USD annuall

Additional Information

We are seeking a recent college graduate (undergrad) who has traversed their academic career learning and experimenting with AI. We want you to bring this new way of thinking to Amazon Ads! You will use these skills to further the development and application of analytics methods to examine the complex data flows of Amazon Ads and to translate deep-dives into actionable insights for our product teams. In this role you will develop new tools to analyze our advertising data to help improve the performance of our bidding algorithms, targeting and relevance systems, help advance our supply strategy, and evaluate the adoption and impact of feature releases. Key job responsibilities Analyze data trends regarding supply, optimization, ad load, and advertising mix effects that affect advertiser performance and contribute to achieving advertiser goals Present papers to senior leaders on issues like feature development impact on identity recognition rates, and changes of ad selection systems to improve fill rate highlighting insights that will inform our business development and engineering roadmaps Formalize our analytics approach to Ads auctions by analyzing bid spreads, auction depth, and simulating impacts of potential auction structure changes Identify, standardize, and operationalize KPIs to effectively measure the performance of all systems involved in ad serving, and use trend insights to inform business priorities Partner with engineering teams to define data logging requirements and getting these prioritized in engineering roadmaps Validate financial models through analysis Develop and own ad revenue and supply intelligence analytics decks that provide ongoing deep-dives A day in the life The Ads Scientist will work closely with business leaders and engineers on developing common data architecture that will optimize our data logging at different grains, and will allow data interoperability from bid flow to optimization to campaign delivery. The candidate will then analyze the data and present papers and ongoing reports on actionable insights.

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