Principal Applied Scientist
Core
Lead high-impact fraud detection initiatives by developing and deploying scalable machine learning solutions that balance detection effectiveness, latency, and operational complexity.
Role type
Principal Applied Scientist (Fraud Detection & Risk Modeling)
Builds
Production-ready ML systems for fraud detection, anomaly detection, and risk modeling
Domain
Financial Services / Fraud Prevention / Machine Learning
Deliverable
production ML models
Required skills
statistical machine learning, anomaly detection, fraud and risk modeling, deep learning, large-scale data mining, causal inference, model operationalization, experimentation frameworks, system design, technical leadership, mentoring
Preferred skills
LLMs, cross-signal analysis, responsible AI practices, scientific rigor
Technologies
LLMs, anomaly detection frameworks, production ML pipelines
Responsibilities
Independently lead and execute multiple high-impact fraud detection initiatives; Develop practical, deployable ML solutions operating reliably at production scale; Translate scientific insights into production impact through rigorous experimentation and monitoring; Drive technical collaboration across science, engineering, ads, security, and privacy teams; Raise the technical bar through mentorship and high standards for quality and governance; Set technical direction and drive multi-year strategy across research and engineering teams.
Seniority
Principal, hands-on IC with strategic leadership
