Principal Applied Scientist, Ads Measurement (GenAI-First)

Amazon Inc.; New York (NY); On-site; USD 219,000 - 296,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Parental leave

Paid time off

Job summary

Amazon Advertising LLC in New York seeks a Principal Applied Scientist to lead measurement science for ads performance across ML, causal inference, NLP and GenAI. You will guide a team of scientists to build scalable measurement products and influence product roadmaps.

As a GenAI-first organization, you will mentor junior members, publish analyses, and collaborate with engineers and product managers to tackle hard problems in advertising measurement.

Qualifications

• 7+ years of hands-on work in predictive modeling and analysis.
• PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field.
• Experience programming in Java, C++, Python or related language.
• Experience leading experienced scientists and mentoring junior members.

Responsibilities

• Drives scientific vision and advises technical leadership on performance measurement models and products.
• Identifies and solves hard, unsolved problems with pragmatic trade-offs.
• Leads cross-team collaboration to align algorithmic strategies and roadmaps.
• Mentors junior scientists and attracts top talent to the organization.
• Contributes to publications and documentation, setting engineering standards.

Skills

Predictive modeling

Programming (Java/C++/Python)

Mentoring

Experimentation

Causal ML

Education

PhD in Electrical Engineering, Computer Science, Mathematics, or related field

Job description

Amazon Advertising LLC in New York seeks a Principal Applied Scientist to lead measurement science for ads performance across ML, causal inference, NLP and GenAI. You will guide a team of scientists to build scalable measurement products and influence product roadmaps.

As a GenAI-first organization, you will mentor junior members, publish analyses, and collaborate with engineers and product managers to tackle hard problems in advertising measurement.