Must Have Technical/Functional Skills
Technical:
• Strong proficiency in Python / R (Pandas, NumPy, Scikit-learn, PySpark)
• Experience with time-series data and event/alarm analytics,sliding winsows, inmemory DB
• Knowledge of machine learning algorithms for classification, clustering, and anomaly detection
• Experience with SQL, big data platforms (Spark, Hadoop),Kafka
• Visualization tools: Tableau, Power BI, Grafana, or Python visualization libraries Domain
• Understanding of Wireless Networks (2G/3G/4G/5G, RAN, Core)
• Knowledge of IEN / IP / Ethernet networking concepts
• Familiarity with network alarms, fault management, OSS/NMS systems
Roles & Responsibilities
Data Analysis & Insight Generation
• 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
Machine Learning & Modeling
• Build models for:
• Alarm correlation and noise reduction
• Root cause analysis (RCA)
• Anomaly detection
• Predictive fault and failure forecasting
• Apply supervised and unsupervised learning techniques (clustering, classification, time-series analysis)
Data Engineering & Automation
• 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