Principal Applied Scientist, Ads Optimization, FAIM

Amazon; Seattle (WA); On-site; USD 199,000 - 269,000; Full time

Benefits offered by this job

RSUs

Health insurance

Career growth

Job summary

Amazon in Seattle seeks a Principal Applied Scientist for Full-Funnel Campaign optimization to invent models that allocate budget across sponsored ad products, maximizing advertiser outcomes and long-term customer value. You will set technical direction for a growing team, prototype and productionize ML and optimization solutions, and guide experiments and measurements across the shopper journey.

The role emphasizes mentorship, collaboration with engineering and product, and publishing impactful

Qualifications

• PhD in a related technical field or equivalent.
• 5+ years in predictive modeling and analysis.
• Ability to translate customer needs into concrete problems.

Responsibilities

• Define long-term scientific vision for full-funnel optimization.
• Invent, prototype, and productionize ML solutions for budget allocation.
• Develop incrementality and long-term sales modeling approaches.
• Design and lead large-scale experiments to guide product direction.
• Partner with engineering and product to deploy models to production.
• Mentor and grow junior scientists; publish research internally.

Skills

PhD required

Predictive modeling

Leadership

Programming: Java/C++/Python

Ambiguity handling

Education

PhD in EE/CS/Math

Tools

Experimentation tools

Job description

Principal Applied Scientist, Ads Optimization, FAIM

Job ID: 10494784 | Amazon.com Services LLC

As a Principal Applied Scientist for Full-Funnel Campaign optimization, you will invent the models that jointly allocate budget across sponsored ad products to maximize advertiser outcomes and long-term customer value. This is a rare charter to build foundational optimization science where little exists today, spanning campaign recommendation, cross-product budget allocation, incrementality measurement, and long-term-sales modeling. You will set technical direction for a growing team, partner with engineering and product to take models from research to production at Amazon scale, and directly move advertiser ROAS and new-to-brand growth.

• Own the science vision for full-funnel campaign optimization end to end
• Invent models for joint budget allocation, incrementality, and long-term value
• Take innovations from prototype to production serving live advertiser campaigns
• Raise the technical bar across scientists and engineers

Key job responsibilities

• Define the long-term scientific vision for full-funnel campaign optimization, translating ambiguous advertiser needs and competing objectives into a concrete science roadmap.
• Invent, prototype, and productionize machine learning and optimization solutions for joint budget allocation across sponsored ad products, spanning the shopper journey from awareness to purchase.
• Develop rigorous approaches to incrementality measurement and long-term-sales modeling that ground optimization in true advertiser value.
• Design and lead large-scale experiments and analyses to validate hypotheses and guide product direction.
• Partner closely with engineering and product to define technical contracts, data schemas, and serving systems that carry models into production.
• Raise the technical bar across science and engineering through mentorship, design reviews, and hands-on collaboration.
• Grow scientific talent and publish impactful research internally and at top-tier venues.

A day in the life
You move between deep technical work and org-wide influence. A morning might be spent deriving a budget-allocation formulation with two scientists, then reviewing an incrementality experiment design over an advertiser segment. Afternoons bring roadmap alignment with product and engineering partners, a design review that raises the bar on a teammate's model, and a working session on taking a prototype to production. Your customers are Amazon advertisers and their shoppers; your stakeholders span applied science, engineering, and product leadership across the Ads full-funnel organization.

About the team
We build the optimization science behind full-funnel advertising on Amazon: how campaigns are recommended, and how budget is allocated across sponsored ad products to grow advertiser outcomes and long-term customer value. Our mission is to make full-funnel advertising work automatically and measurably for every advertiser, from foundational research through production systems serving live campaigns. We are a science-driven, high-ownership team that values rigorous experimentation, invention where no proven approach exists yet, and close partnership with engineering and product.

Basic Qualifications

• PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
• 5+ years of hands-on experience in predictive modeling and analysis
• Experience distilling informal customer requirements into problem definitions while dealing with ambiguity and competing objectives
• Experience programming in Java, C++, Python, or related language
• Experience leading experienced scientists, as well as a record of developing junior members from academia or industry into a career track in a business environment

Preferred Qualifications

• 10+ years of relevant experience in industry or academia
• Knowledge of problem solving, algorithm design, and complexity analysis
• Experience creating novel algorithms and advancing the state of the art
• 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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, Palo Alto - 228,700.00 - 309,400.00 USD annually

USA, WA, SEATTLE - 198,900.00 - 269,000.00 USD annually

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.