Applied Scientist II, Predictive Targeting

Amazon Science; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

RSUs/sign-on

Job summary

Amazon Science in Seattle, WA is seeking an Applied Scientist to advance targeting for Amazon’s marketing initiatives across channels and ad formats. You will turn business questions into modeling problems and guide solutions from prototype to production while collaborating with senior scientists and engineers.

You will work on online optimization, incrementality modeling, and agentic workflows that make science recommendations actionable for business partners.

Qualifications

• 3+ years building models for business applications.
• Experience with patents or publications in top-tier conferences or journals.
• Proficiency in Java, C++, Python or related language.
• Experience in algorithms, data structures, numerical optimization, data mining, parallel and distributed computing, HPC.
• PhD or Master’s + 3+ years applied research experience.

Responsibilities

• Build online optimization (e.g., TSO, bandits) and reinforcement learning methods to optimize targeting outcomes.
• Develop incrementality and uplift models to estimate causal impact of targeting.
• Improve the segment-based targeting model with new features and architectures.
• Contribute to the intelligence layer of the agentic system and explain targeting decisions.
• Design and analyze experiments (A/B tests, causal inference) to measure impact.
• Write production-quality model code and deploy with engineers.
• Present methods and results with data-driven recommendations.

Skills

Modeling for business applications

Java

C++

Python

Algorithms & data structures

Numerical optimization

Data mining

Parallel & distributed computing

High-performance computing

Reinforcement learning

Education

PhD or Master's with 3+ years of applied research

Tools

Unix/Linux

Job description

Description

Are you passionate about using data and machine learning to improve how Amazon reaches customers? The Customer Targeting team is looking for an Applied Scientist to build the science behind the targeting of Amazon's marketing initiatives across channels and ad formats. You will turn business questions into modeling problems and take your solutions from prototype to production, working closely with senior scientists, engineers, and business partners.

We are moving targeting toward outcome-based optimization and an AI-native, agentic way of working. In this role you will work on online optimization and reinforcement learning, incrementality modeling, and the next generation of our segment-based targeting model. You will also help build agentic workflows that make targeting decisions transparent and bring science recommendations to the people using them.

The right candidate has strong quantitative and statistical skills, hands‑on experience with modern ML methods, and is comfortable working through ambiguity in a fast‑paced environment. You pay close attention to detail, learn quickly, and work well in a highly collaborative team.

Key job responsibilities

• Build online optimization (e.g., TSO, bandits) and reinforcement learning methods that optimize targeting decisions for business outcomes rather than proxy metrics.
• Develop incrementality and uplift models that estimate the causal impact of targeting, and use them to improve who we target and how much we spend.
• Improve the existing segment‑based targeting model: engineer and evaluate new features, migrate it to new model architectures, and build automated feedback loops that retrain and improve the model from observed outcomes.
• Contribute to the intelligence layer of our agentic system: build components that explain targeting decisions and propose science‑driven solutions to business partners.
• Design and analyze experiments (A/B tests, causal inference methods) to measure the incremental impact of targeting changes.
• Write production‑quality model code and partner with engineers to deploy, monitor, and maintain models.
• Present methods and results clearly, backed by data, with actionable recommendations for science and business stakeholders.

About The Team

Predictive Targeting builds the systems that decide who sees Amazon's marketing content, and how often, across Amazon's stores and channels. We are engineers and scientists working on one shared problem: making sure customers see the most relevant and engaging marketing, and making each campaign better than the last.

Basic Qualifications

• 3+ years of building models for business application experience
• Experience in patents or publications at top‑tier peer‑reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing
• PhD, or Master's degree and 3+ years of applied research experience

Preferred Qualifications

• Experience using Unix/Linux
• Experience in professional software development
• Experience creating processes and improving tools that have measurably improved productivity, quality, or advertiser experience
• PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or experience in defining and creating benchmarks for assessing GenAI model performance
• Experience with reinforcement learning or online optimization in production, such as multi‑armed or contextual bandits, exploration vs. exploitation strategies, or real‑time pacing and allocation under budget and frequency constraints.

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, WA, Seattle - 142,800.00 - 193,200.00 USD annually