DESCRIPTION The Automated Profitability Management (APM) team's vision is to offer the world's most advanced suite of products to optimize and manage the contractual agreements between a retailer and its suppliers.
Our teams build software and machine learning models to optimize contract negotiations, and exchange of goods between Amazon Retail and tens of thousands of brands offering millions of products available to hundreds of millions of Amazon customers worldwide. We handle product costs (How much should Amazon pay for this product?) but also cover supply chain (Who pays the initial shipping costs?), marketing (Should a vendor fund advertising?), reverse-logistics (Who pays for damaged products? What about unsold inventory?) and more.
Our mission is to provide to our customers the world's largest product assortment at competitive prices, through long term partnership with our vendors.
Key job responsibilities
Develop, prototype, and deploy machine learning models to improve our understanding of product cost drivers and optimize negotiation strategies with vendors.
Guide the multi-year vision for science investments within APM across core negotiation systems, and contract systems.
Raise the technical bar for the other scientists and machine learning engineers in the organization.
Collaborate with product managers, applied scientists, economists, and software developers to incorporate models into production processes.
Represent APM in front of senior Amazon Retail leaders and internal partners to articulate how science investments can improve selection available to customers.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA BASIC QUALIFICATIONS Graduate degree in Statistics, Machine Learning, Applied Mathematics, or a related field.
8+ years of relevant experience in industry, consulting, government, or academic research.
3+ years of experience in building machine learning models for business application.
Fluency in Python, Java, or related language.
Subject matter expert in machine learning techniques for prediction, classification, and/or optimization problems.