Staff Data Scientist - Digital Intelligence
Core
Lead the development of production-grade fraud and identity risk signals by transforming high-scale device, network, browser, mobile, and behavioral telemetry into actionable intelligence.
Role type
Staff Data Scientist (Technical Leadership & Signal Development)
Builds
Production risk signals, models, and feature engineering pipelines for fraud detection and identity verification
Domain
Cybersecurity, Fraud Detection, Digital Identity, Risk Modeling
Deliverable
production ML models
Required skills
Production ML model deployment, Feature engineering, Anomaly detection, Statistical modeling, SQL, Python, Distributed data processing (Spark/PySpark), Model evaluation, Adversarial behavior analysis
Preferred skills
Device intelligence, Behavioral biometrics, Graph-based risk signals, Streaming/low-latency decisioning, Privacy-preserving ML, ML frameworks (TensorFlow/PyTorch)
Technologies
Spark, PySpark, scikit-learn, XGBoost, TensorFlow, PyTorch
Responsibilities
Lead high-impact ML and feature-development initiatives across device, network, and behavioral intelligence; Own ambiguous fraud and identity risk problems; Develop production risk signals balancing detection and false-positive risk; Build scalable feature-engineering approaches for noisy telemetry; Investigate complex signal patterns like spoofing and proxy usage; Define evaluation methods including drift monitoring and adversarial robustness; Mentor data scientists on problem framing and validation rigor
Seniority
Staff, Technical Leadership & Mentorship
