Principal Applied Scientist, Ads Optimization, FAIM

Amazon
Palo Alto, CA, USA / Seattle, WA, USA2026-08-06ONSITE

About the job

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.

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.

Qualifications

Minimum

- 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

- 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