Senior Applied Scientist, Advertising
Core
Design and implement deep learning models to optimize ad matching for Amazon's programmatic advertising products, predicting customer propensity to convert using behavioral and contextual data.
Role type
Senior Applied Scientist (Advertising/Recommendation Systems)
Builds
Machine learning models for performance sourcing and ad matching across multiple verticals and geographies
Domain
Programmatic Advertising / Machine Learning
Deliverable
production ML models
Required skills
Deep learning, multi-task learning, Java/C++/Python, neural networks, large-scale data processing, quantitative analysis
Preferred skills
Distributed systems (Hadoop, Spark), modeling tools (TensorFlow, PyTorch, scikit-learn, MxNet), R, numpy, scipy
Technologies
TensorFlow, PyTorch, Java, C++, Python, Hadoop, Spark, MxNet, scikit-learn, numpy, scipy
Responsibilities
Design and implement deep learning models for ad matching; Investigate new ML techniques like multi-task learning; Improve model performance and scalability; Prototype and test hypotheses in high-ambiguity environments; Partner with engineering to deploy code changes; Align with advertiser objectives to drive long-term product capabilities
Seniority
Senior, hands-on IC with research leadership
