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Applied Scientist II, Predictive Targeting

Amazon

Seattle, WAJob$143–193K/yrSeen 1w agoSeen in employer's feed 4 days ago

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At a glance

Compensation
$143–193K/yr
Location
Seattle, WA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Applied Scientist will build and deploy science for Amazon’s marketing targeting across channels and ad formats. The role focuses on online optimization, reinforcement learning, incrementality modeling, and segment-based targeting, while contributing to agentic workflows that explain decisions and surface recommendations. The scientist will work with engineers, senior scientists, and business partners to measure outcomes, improve models, and communicate actionable findings.

Skills & qualifications

RequiredNice to have

Skills

Quantitative SkillsStatistical SkillsMachine LearningModel BuildingJavaC++PythonAlgorithms and Data StructuresParsingNumerical OptimizationData MiningParallel and Distributed ComputingHigh-Performance ComputingUnix/LinuxProfessional Software DevelopmentProcess ImprovementTool ImprovementBenchmark CreationReinforcement LearningOnline OptimizationMulti-Armed BanditsContextual BanditsExploration-Exploitation StrategiesReal-Time Pacing and Allocation

Qualifications

3+ Years Model BuildingPatents or Top-Tier PublicationsPhD or Master's and 3+ Years Applied ResearchPhD in Quantitative FieldStatisticsMathematicsData ScienceBusiness AnalyticsEconomicsFinanceEngineeringComputer Science

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off
Parental Leave

Full 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

How this job compares

Set against the 1,220 open Applied Scientist jobs on Olive Jobs, counted October 27, 2026.

Pay
  • This posting$143–193K/yr
  • Washington median$143–226K/yr257 salary ranges
  • US median$158–264K/yr1,178 salary ranges

This range's midpoint, $168K, is 15% below the Washington median midpoint ($197K) — in the middle half of Applied Scientist salary ranges in Washington.

Openings
Olive Jobs lists 263 open Applied Scientist jobs in Washington and 1,220 across the US. Under 1% of them nationwide are listed as remote or flexible.
Hiring the most in Washington
Experience
This posting asks for at least 3 years of experience; Applied Scientist postings that state a minimum ask for 5 years at the median (1,007 postings).
Education
732 of the 1,220 open Applied Scientist jobs (60%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on October 27, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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