Applied Scientist, Bidding Science and Experimentation

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. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Bidding Experimentation and Science Team is responsible for both real-time pricing and ranking decisions on the Amazon RTB (Real-Time Bidding) system as well as our experimentation infrastructure and methodology. As the owners of ranking, we have one of the most important job in the DSP which is to set the bid price on advertising opportunities. Even small incremental improvement is making a huge impact for the company, and we are responsible for developing the next generation of pricing algorithms to drive these improvements. As owners of experimentation, we work closely with not only scientists within our team but also our partners teams to develop new online experiment designs, propose new analysis methodologies to increase the statistical validity and power of our results, and build tools to enable experimenters to rapidly iterate on their ideas. Experimentation is ultimately the engine that drives our decision-making when launching new products and algorithms. The visibility of our team's work is very high and we receive high support from the management and peer teams. These systems are optimizing the price of every individual opportunity on behalf of Amazon Advertising advertisers.

You will play a significant role in building and improving our production algorithms, leveraging the latest advances in ML, online optimization, optimal control, forecasting, and causal inference, to name a few. You will construct prototypes to validate your hypotheses, work with engineers to turn these prototypes into production systems, and perform offline analysis and online A/B experimentation. You will also join the Amazon science community, with opportunities to write papers, attend workshops and conferences (internal and external), participate in science events, and obtain early access to Amazon ML technologies.

Be a technical leader in ML, optimization, and causal inference and drive full life-cycle projects within this team and across other teams

Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.

Develop algorithms for online optimization and control, bandits, and reinforcement learning and bring them to production.

Develop, design, and run A/B experiments, gather data, and perform statistical analysis.

Establish scalable, efficient, automated processes for monitoring and feedback.

Work closely with software engineers to assist in productionizing your work.

Research new and innovative machine learning and optimization approaches.

Recruit Applied Scientists and Data Scientists to the team and mentor scientists on the team.