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Data Engineer- PySpark/Apache Flink
Diverse Lynx
- United States
- United States
À propos
Skills: Digital : Python for Data Science~5G Wireless Networks Experience Required: 8-10
Role Descriptions: Data Analysis Insight GenerationAnalyze large-scale wireless (RAN| Core) and IEN network alarm data from OSSNMS systems Identify patterns| trends| and recurring fault signatures across network domains Develop KPIs and dashboards to track network health and fault trendsMachine Learning ModelingBuild models for Alarm correlation and noise reductionRoot cause analysis (RCA)Anomaly detectionPredictive fault and failure forecastingApply supervised and unsupervised learning techniques (clustering| classification| time-series analysis) Data Engineering AutomationClean| normalize| and enrich alarm data from multiple sources Integrate data from OSS| EMS| NMS| CMDB| and performance systemsKey responsibilitiesData Analysis Insight GenerationAnalyze large-scale wireless (RAN| Core) and IEN network alarm data from OSSNMS systems Identify patterns| trends| and recurring fault signatures across network domains Develop KPIs and dashboards to track network health and fault trendsMachine Learning ModelingBuild models for Alarm correlation and noise reductionRoot cause analysis (RCA)Anomaly detectionPredictive fault and failure forecastingApply supervised and unsupervised learning techniques (clustering| classification| time-series analysis) Data Engineering AutomationClean| normalize| and enrich alarm data from multiple sources Integrate data from OSS| EMS| NMS| CMDB| and performance systems Essential Skills: Data Analysis Insight GenerationAnalyze large-scale wireless (RAN| Core) and IEN network alarm data from OSSNMS systems Identify patterns| trends| and recurring fault signatures across network domains Develop KPIs and dashboards to track network health and fault trendsMachine Learning ModelingBuild models for Alarm correlation and noise reductionRoot cause analysis (RCA)Anomaly detectionPredictive fault and failure forecastingApply supervised and unsupervised learning techniques (clustering| classification| time-series analysis) Data Engineering AutomationClean| normalize| and enrich alarm data from multiple sources Integrate data from OSS| EMS| NMS| CMDB| and performance systemsKey responsibilitiesData Analysis Insight GenerationAnalyze large-scale wireless (RAN| Core) and IEN network alarm data from OSSNMS systems Identify patterns| trends| and recurring fault signatures across network domains Develop KPIs and dashboards to track network health and fault trendsMachine Learning ModelingBuild models for Alarm correlation and noise reductionRoot cause analysis (RCA)Anomaly detectionPredictive fault and failure forecastingApply supervised and unsupervised learning techniques (clustering| classification| time-series analysis) Data Engineering AutomationClean| normalize| and enrich alarm data from multiple sources Integrate data from OSS| EMS| NMS| CMDB| and performance systems Desirable Skills:
Compétences linguistiques
- English
Avis aux utilisateurs
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