Senior Applied Scientist - Ads Ranking & Retrieval
Core
Develop and productionize identity-clustering, applicant-risk, and behavioral detection models to identify abuse patterns and active accounts using machine learning.
Role type
Senior Applied Scientist (Ads Ranking & Retrieval / Risk Detection)
Builds
Production ML models for identity clustering, risk scoring, and abuse detection
Domain
Online advertising, fraud detection, security
Deliverable
production ML models
Required skills
Python, R, Scala, graph neural networks, embedding-based entity linkage, sequence and time-series modeling, adversarial machine learning, anomaly detection, feature engineering, experimental design, causal inference, model calibration
Preferred skills
LLM-assisted enrichment, API abuse defense, scraping defense, model extraction/distillation defense, privacy and compliance constraints
Technologies
Python, R, Scala
Responsibilities
Develop identity-clustering models using similarity, graph, and embedding methods; Build behavioral detection for active accounts using sequence modeling and anomaly detection; Train, tune, and validate detection models with feature engineering and adversarial testing; Investigate live abuse patterns and conduct offline/online experiments; Work with product and engineering counterparts to productionize model decisions
Seniority
Senior, hands-on IC
