Senior Applied Science Manager, Traffic Quality
Core
Define long-term science vision and lead teams in building advanced capabilities to detect sophisticated invalid traffic (IVT), including non-human traffic and bot networks, across billions of daily ad events using deep learning and generative modeling.
Role type
Senior Applied Science Manager (Traffic Quality)
Builds
Production-level ML solutions and monitoring systems for advertiser trust and marketplace integrity
Domain
Programmatic advertising, invalid traffic detection, deep learning, generative modeling
Deliverable
production ML models
Required skills
strategic leadership, statistical and machine learning solution design, full development cycle ownership (design, prototype, A/B testing, deployment), team hiring and management, scientific standard setting, experiment scoping, root cause analysis, precision-recall trade-offs
Preferred skills
big data application, predictive modeling, big data technologies (AWS, Hadoop, Spark, Pig, Hive), programming (Java, C++, Python, R, MATLAB), PhD in CS/ML/AI/Statistics
Technologies
AWS, Hadoop, Spark, Pig, Hive, Java, C++, Python, R, MATLAB
Responsibilities
Define long-term science vision and translate it into actionable team plans; Design and implement statistical and ML solutions for traffic pattern detection; Own full development cycle for production code handling billions of requests; Hire, manage, coach, and promote scientists; Maintain near real-time monitoring systems and respond to anomalies; Partner with cross-functional teams to solve complex IVT detection problems
Seniority
Senior, hands-on IC with people management
