Pricing Optimization Scientist, Pricing Science
Core
Build sequential decision-making methods (contextual bandits, reinforcement learning, online optimization) to set optimal prices for Amazon's catalog, handling delayed rewards, noisy signals, and hard business constraints.
Role type
Applied Scientist (Pricing Optimization)
Builds
Pricing policies and optimization systems that run at Amazon scale
Domain
E-commerce, Pricing Science, Reinforcement Learning
Deliverable
production ML models
Required skills
sequential decision-making, contextual bandits, reinforcement learning, online optimization, numerical optimization, algorithms and data structures, parallel and distributed computing, Java, C++, Python
Preferred skills
professional software development, Unix/Linux, architectural concepts
Technologies
Java, C++, Python, Unix/Linux
Responsibilities
prototype and stress-test pricing policies in simulation, design reward signals for delayed feedback, review online experiment readouts, write science proposals for new constraints, pair with engineers to optimize policy speed, present findings at science reviews
Seniority
Senior, hands-on IC