experience in Data Science / Statistical Modeling
Apply statistical modeling and data science techniques to transaction and TCP L4 telemetry to identify anomalous traffic and behavioral patterns.
Build behavioral baselines and anomaly detection models using time-series analysis, clustering, correlation, outlier detection, and statistical thresholds.
Engineer features from transaction, connection, velocity, retry, batch, and historical alert data.
Develop statistical scoring and classification models to identify legitimate, duplicate, retry, anomalous, and potential DDoS activity.
Analyze historical incidents and alerts to optimize detection thresholds and reduce false positives.
Integrate statistical detection signals into agentic AI investigation workflows for automated correlation, investigation, and evidence generation.
Validate models using historical and simulated traffic scenarios.
Measure precision, recall, false-positive/false-negative rates, and detection latency.
Monitor model performance, behavioral drift, and changes in traffic patterns.
Continuously tune detection algorithms based on traffic behavior and model performance.
Partner with engineering and operations teams to productionize models.
Provide explainable, statistically grounded recommendations to human investigators.
MS in statistics, data science- related
12+ years experience