Principal Applied Scientist, Ads Optimization, FAIM

Description

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.

• 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 product ionize 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.

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.

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.

• 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

• 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…