Applied Scientist II, Predictive Targeting
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $142,800 to $193,200
Employer-published annual base salary, USD. Advertised base range in Seattle, WA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSeattle, WA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (35 min ago) · observed since
About this job
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
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($142,800) is above 26% of the 324 Data & ML roles in Washington listed on this site; 69 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $168,100.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.
This listingApplied Scientist II, Predictive Targeting$142,800 to $193,200
Customer Insights Lead, Global Logistics Domestic First Mile$142,800 to $193,200
Senior Product Marketing Manager, GTM Lead, Fashion & Fitness Marketing$142,800 to $193,200
Applied Scientist, BRP Payment Risk ML, BRP Payment Risk ML$142,800 to $193,200
Applied Scientist, Denied Party Screening (DPS), AWS Compliance & Security Assurance$142,800 to $193,200
Simulation & Modeling Applied Scientist, Prime Air Flight Sciences High Fidelity Methods$142,800 to $193,200
Applied Scientist, AWS Payments and Fraud Prevention$142,800 to $193,200
Chart as a table
| Role | Published base |
|---|---|
| Applied Scientist II, Predictive Targeting (this listing) | $142,800 - $193,200 |
| Customer Insights Lead, Global Logistics Domestic First Mile | $142,800 - $193,200 |
| Senior Product Marketing Manager, GTM Lead, Fashion & Fitness Marketing | $142,800 - $193,200 |
| Applied Scientist, BRP Payment Risk ML, BRP Payment Risk ML | $142,800 - $193,200 |
| Applied Scientist, Denied Party Screening (DPS), AWS Compliance & Security Assurance | $142,800 - $193,200 |
| Simulation & Modeling Applied Scientist, Prime Air Flight Sciences High Fidelity Methods | $142,800 - $193,200 |
| Applied Scientist, AWS Payments and Fraud Prevention | $142,800 - $193,200 |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-10-15
Where this pay comes from
Location as the employer wrote it: US, WA, Seattle
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
