Principal Applied Scientist, Ads Optimization, FAIM

About the role

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

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.

Qualifications

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

Pay

USA, CA, Palo Alto - $228,700.00 - $309,400.00 USD annually

USA, WA, Seattle - $198,900.00 - $269,000.00 USD annually

Benefits

• Sign-on payments and restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans)
• Employee Assistance Program (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 amazon.jobs/en/benefits.