About this opportunity
Amazon.com Services LLC lists this Applied Science Manager, CBA opportunity in seattle, Washington. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Amazon is hiring a Manager to lead a science team within Customer Forecasting and Valuation (CFV). CFV owns several of the primary decision metrics Amazon uses to evaluate launches and investments — causal estimates of how customer actions today translate into customer value over the year ahead. These metrics are how Amazon works backwards from the customer at scale: they let thousands of launch decisions a year, across Retail, Ads, Marketing, and Selection, weigh short-term profitability against long-term growth.
We are in the middle of a generational rebuild of how these metrics are produced. Our team is developing transformer-based foundation models of customer behavior, learned directly from billions of behavioral events. They are being built as shared infrastructure: one learned representation of customer behavior that a wide range of measurement and optimization systems across Amazon can be built on top of.
CFV is part of the Customer Behavior Analytics (CBA) organization, which builds the tools used to understand customer behavior and value generation across Amazon's Retail business.
As a manager in CFV, you will lead Applied Scientists, Economists, and Data Scientists working at the intersection of causal inference, sequence modeling, and experimentation. The work spans methodological invention — making learned representations estimation-aware, closing the loop between experimental ground truth and model training, extrapolating short-horizon observations into year-ahead causal effects — and translation of that work into production systems that move real launch decisions. You will set multi-year research and product agendas in partnership with senior scientists, product owners, and business leaders, and you will work closely with a dedicated engineering team.
The right candidate has deep expertise in ML and causal inference, judgment about when to invent versus reuse, and the appetite to operate in ambiguity. If you want to lead a team shaping how Amazon measures the value of what it does for customers, and how it balances short-term profitability with long-term growth, we should talk.
BASIC QUALIFICATIONS
- 3+ years of scientists or machine learning engineers management experience
- PhD, or Master's degree
- Knowledge of machine learning approaches and algorithms
PREFERRED QUALIFICATIONS
- 5+ years of building machine learning models or developing algorithms for business application experience
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at .
USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually
Worksite address
seattle, WA, 98127, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.