Data Scientist, Traffic Quality
Core
Build advanced capabilities at petabyte scale to detect sophisticated invalid traffic (IVT), including non-human traffic, bot networks, and fraudulent engagement patterns in programmatic advertising.
Role type
Senior IC data scientist (fraud detection & ML research)
Builds
Detection systems for invalid traffic across Amazon Ads properties
Domain
Advertising technology, fraud detection, deep learning
Deliverable
production ML models
Required skills
advanced statistical techniques, machine learning, deep learning, generative modeling, user behavior analysis, multi-modal representation learning, anomaly detection, time-series analysis, sparse labeling methods, SQL, Python, R, SAS, Matlab
Preferred skills
defining and framing new research problems, creating mathematical textbooks or research papers, mentoring junior scientists, evaluating AI systems, applying theoretical models in applied environments, defining benchmarks for GenAI model performance, cross-disciplinary project leadership
Technologies
EC2, S3, EMR, Sagemaker, RedShift
Responsibilities
Define and frame new research problems in fraud detection where neither problem nor solution is well-defined; Apply new machine learning approaches, models, and algorithms to detect sophisticated invalid traffic; Work with unstructured and massive datasets to deliver results; Produce research reports meeting top-tier external publication standards; Mentor and develop junior scientists on the team
Seniority
Senior, hands-on IC with mentorship responsibilities
