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.

Preferred Qualifications

PhD in Statistics, Machine Learning, Applied Mathematics, or a related field.

Proven ability to mentor and develop junior scientists

Excellent written and verbal technical communication with both technical and business audience.

Expertise in causal modeling in observational setting.

Hands-on experience in economic optimization, and Large Language Models (LLMs)

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $196,900/year in our lowest geographic market up to $340,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.