Applied Scientist II, Advertising Incrementality Measurement
Core
Lead the development of scientifically rigorous causal inference models to measure the effectiveness of Amazon Ads and guide advertiser decisions.
Role type
Senior Applied Scientist (Causal Inference & ML)
Builds
Customer-facing advertising measurement tools and internal research frameworks
Domain
Digital Advertising, Causal Inference, Machine Learning
Deliverable
production ML models
Required skills
Causal inference, Deep Learning, Machine Learning, Econometric modeling, Java, C++, Python, Algorithms and data structures, Numerical optimization, Data mining, Parallel and distributed computing, High-performance computing
Preferred skills
Unix/Linux, Professional software development
Technologies
Java, C++, Python
Responsibilities
Develop novel scientific models describing advertising impact on customer actions, Own end-to-end development of models for business stakeholders, Improve and simplify existing solutions and frameworks, Review and audit modeling processes and results, Align scientific developments with business strategy, Identify new opportunities from data insights, Develop and document scientific research
Seniority
Senior, hands-on IC