The Pricing and Promotions Optimization Science team is hiring an incrementality applied scientist with experience in causal inference experimentation and ML development to help us expand our causal modeling solutions for understanding promotion effectiveness. Our work is foundational to providing sellerfacing promotional tools furthering internal research & development and building out Amazons promotion optimization measurement offerings. Incrementality measurement is a pin for the next generation of Amazon Promotion solutions and this role will play a key role in the release and expansion of these offerings.
Partner with principals and senior team members to drive science improvements and implement technical solutions at the stateoftheart of machine learning and econometrics Partner with engineering and other science collaborators to design implement prototype deploy and maintain largescale causal ML models. Carry out indepth research and analysis exploring promotionrelated data sets including large sets of realworld experimental data to understand behavior highlight model improvement opportunities and understand shortcomings and limitations. Define data quality standards for understanding typical behavior capturing outliers and detecting model performance issues. Work with product stakeholders to help improve our ability to provide quality measurement of promotion effectiveness for our customers.
About the team The Pricing and Promotions Optimization science team owns price quality discovery and discount optimization initiatives across Amazons internal pricing and promotions architectures as well as upwards into the customer discovery funnel. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing elasticity estimation product substitutability and optimization. We preserve long term customer trust by ensuring Amazons prices and promotions are always competitive and error free.
3 years of building models for business application experience PhD or Masters degree and 4 years of CS CE ML or related field experience Experience programming in Java C Python or related language Experience in designing experiments and statistical analysis of results
Experience in professional software development Knowledge of architectural concepts and algorithms schedule tradeoffs and new opportunities with technical team members 2 years of designing experiments and statistical analysis of results experience 2 years of handson predictive modeling and large data analysis experience
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