Senior Applied Scientist, CBA

Amazon Science; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

RSUs

Health insurance

Paid time off

Job summary

Amazon Science in Seattle is seeking a Senior Applied Scientist within Customer Forecasting and Valuation (CFV). You will work at the intersection of causal inference, sequence modeling, and experimentation to produce year-ahead customer value metrics used across Retail, Ads, Marketing, and Selection.

You will partner with senior scientists, product owners, and engineers to translate research into production systems that guide launch decisions and long-term growth, balancing short-term

Qualifications

• 4+ years of applied research experience.
• 3+ years building ML models for business applications.
• PhD, or MS with 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Work at the intersection of causal inference, sequence modeling, and experimentation.
• Partner with other senior scientists, product owners, and business leaders to translate research into production systems.
• Design and evaluate year-ahead metrics to guide launches and investments.

Skills

Applied research

ML models

Java

C++

Python

Neural networks

Education

PhD or MS with 6+ years of applied research experience

Tools

TensorFlow

PyTorch

Job description

Description

Amazon is hiring a Senior Applied Scientist 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.

Description

Amazon is hiring a Senior Applied Scientist 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 Senior Applied Scientist you are 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 partner with other 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 be part of a team that is 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

• 4+ years of applied research experience
• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Have peer-reviewed scientific contributions in premier journals and conferences

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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 https://amazon.jobs/en/benefits. USA, CA, Sunnyvale - 192,200.00 - 260,000.00 USD annually USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually