Description

Job Description

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 to improve detection accuracy.Develop statistical scoring and classification models to differentiate 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 and measure precision, recall, false-positive/false-negative rates and detection latency.Monitor model performance, behavioral drift and changes in traffic patterns and continuously tune detection algorithms.Partner with engineering and operations teams to productionize models and provide explainable, statistically grounded recommendations to human investigatorsWork Experience 7-10Years

Key Skills

Education

Bachelor's degree