Role: Data Scientist – Network Fault Management (Wireless & IEN Alarms)
Location: Basking Ridge, NJ
Duration: Long term Contract
• Analyze large-scale wireless (RAN, Core) and IEN network alarm data from OSS/NMS systems
• Identify patterns, trends, and recurring fault signatures across network domains
• Develop KPIs and dashboards to track network health and fault trends
• Build machine learning models for alarm correlation, noise reduction, root cause analysis, anomaly detection, and predictive fault forecasting
• Apply supervised and unsupervised learning techniques such as clustering, classification, and time-series analysis
• Clean, normalize, and enrich alarm data from multiple sources
• Integrate data from OSS, EMS, NMS, CMDB, and performance systems
• Automate fault insight pipelines and model deployment
• Collaborate with NOC, Network Engineering, and Reliability teams to translate analytical findings into operational recommendations
• Support proactive maintenance and incident prevention initiatives
• Create interactive dashboards and reports for real-time fault monitoring
• Present insights clearly to technical and non-technical stakeholders
• Strong proficiency in Python or R (Pandas, NumPy, Scikit-learn, PySpark)
• Experience with time-series data and event/alarm analytics
• Knowledge of machine learning algorithms for classification, clustering, and anomaly detection
• Experience with SQL and big data platforms such as Spark or Hadoop
• Familiarity with visualization tools like Tableau, Power BI, Grafana, or Python visualization libraries
• Understanding of wireless networks (2G/3G/4G/5G, RAN, Core)
• Knowledge of IEN/IP/Ethernet networking concepts
• Familiarity with network alarms, fault management, and OSS/NMS systems
• Understanding of MTTR, SLA, availability, and reliability metrics
• Strong analytical and problem-solving skills
• Ability to communicate insights effectively and work in cross-functional operational teams
• Experience in telecom, ISP, or network operations environments preferred
• Knowledge of AIOps or network intelligence platforms preferred
• Experience with real-time streaming data tools such as Kafka or Flink preferred
• Exposure to ITIL and incident/problem management frameworks preferred
• Deliverables include alarm correlation and RCA models reducing false positives, predictive fault alerts improving proactive maintenance, operational dashboards for NOC and engineering teams, and documentation with model performance reports