The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. We are seeking an Applied Scientist to join our Supply Science team. This team is within the Sponsored Products team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant ads on the Amazon search page world-wide thereby enhancing the shopper experience. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference and data engineering. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking an Applied Scientist to join a team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions of customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As an Applied Scientist on this team you will: * Drive end-to-end machine learning projects that have a high degree of ambiguity, scale and complexity * Perform analysis on very large data sets to develop ideas and size opportunities; build machine learning models and conduct analysis to demonstrate potential business value * Design A/B experiments, working with engineers to launch online experiments; conduct statistical analysis of the experimental results to derive understanding * Build efficient and automated processes for large-scale feature generation, machine-learning model training, validation and serving. Work with engineers to productionize ML models. * Develop new and innovative machine learning approaches, and collaborate with the science community. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail and an ability to work in a fast-paced environment. Some examples of day-to-day activities include: * Dive deep into the data to understand business opportunities and formulate the science problems * Implement/create ML models to fit the observed data and predict customer response * Conduct offline analysis to gauge business impact * Communicate with PMs and engineers to discuss experiment plans and outcomes * Work with engineers to conduct A/B tests or productionize your models. * Collaborate with others scientists on problem solving and knowledge sharing. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon.