Applied Scientist, Large-Scale Ads ML & Optimization

Amazon Inc.; San Francisco (CA); On-site; USD 172,000 - 222,000; Full time

Job summary

Amazon Ads is hiring an Applied Scientist to own science for supply-optimization problems, taking work from framing to experimentation and production with measurable business impact.

You will collaborate with software engineers and product managers to productionize models and tie science to advertiser outcomes. The role emphasizes high-rigor applied science at scale within a fast-growing Amazon Ads team.

Qualifications

• 3+ years of building models for business application experience.
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

Responsibilities

• Conduct hands-on data analysis and build large-scale ML models and pipelines for supply optimization.
• Take models end-to-end from proof of concept through experimentation and deployment—productionize with engineers and product managers.
• Design and run A/B experiments and causal analyses to validate hypotheses and measure business impact.
• Research and apply advanced ML, including generative AI and large language models, to demand prediction and traffic filtering.
• Drive end-to-end optimization projects, creating scalable processes for model dev, validation, and deployment.

Skills

Modeling experience

Data analysis

Education

PhD or MS + 4+ years CS/CE/ML

Tools

Java

C++

Python

Job description

Amazon Ads is hiring an Applied Scientist to own science for supply-optimization problems, taking work from framing to experimentation and production with measurable business impact.

You will collaborate with software engineers and product managers to productionize models and tie science to advertiser outcomes. The role emphasizes high-rigor applied science at scale within a fast-growing Amazon Ads team.