DESCRIPTION

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Amazon Advertising is at the forefront of shaping the future of advertising technology, and our Response Prediction and Auction Science team in Sponsored Brands is pivotal in driving this innovation.

SB Response Prediction and Auction Science Team predicts how shoppers interact with Sponsored Brands ads and designs auction systems to drive values for advertisers, shoppers and Amazon ads. We collaborate with different teams across the Amazon ads to build scalable online and offline ML infrastructure systems to accelerate science innovations, facilitate business growth and promote technology innovation.

Key job responsibilities
As an Applied Scientist on this team, you typically play a key role in optimizing ad delivery, improving targeting accuracy, and maximizing revenue generation for advertisers, all while maintaining a seamless user experience, you will:

Develop optimization techniques (e.g., multi-objective optimization) to balance multiple goals, such as maximizing revenue for advertisers, increasing user engagement, and maintaining fair ad distribution.

Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.

Run A/B experiments, fine-tune the models for real-world effectiveness, ensuring that the ad auction system works optimally in production environments.

Run large-scale experiments to test different auction strategies, bidding algorithms, and ad targeting techniques, using methodologies like multi-arm bandit or reinforcement learning.
Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving

Communicate results and insights clearly to non-technical stakeholders, including product managers, advertisers, and executives, helping them understand the impact of data-driven decisions.

Research new and innovative machine learning approaches.