Description

Analyze wireless network alarm data to identify fault patterns, build ML models for root cause analysis, and automate data pipelines to reduce MTTR.

This role is on-site.

Responsibilities

• Analyze large-scale alarm data from RAN, Core, and IEN domains to identify recurring fault signatures and trends.
• Develop machine learning models for alarm correlation, noise reduction, false-positive suppression, and predictive fault forecasting.
• Build and maintain interactive dashboards using Tableau, Power BI, or Grafana for real-time fault monitoring.
• Automate data pipelines and model deployment workflows using Python, R, and big data platforms.
• Collaborate with NOC and Network Engineering teams to translate analytical insights into actionable operational recommendations.

Required Skills

• 5+ years of experience in data engineering or network analytics.
• Proficiency in Python and R with Pandas, NumPy, and Scikit-learn.
• Experience with PySpark, Spark, and Hadoop for big data processing.
• Ability to build visualizations using Tableau, Power BI, or Grafana.
• Understanding of wireless network technologies (2G-5G, RAN, Core, IEN).
• Strong SQL skills for querying and analyzing complex datasets.
• Experience with supervised and unsupervised learning techniques.

Preferred Skills

• Familiarity with OSS/NMS platforms and fault management processes.
• Experience with real-time streaming data technologies.

Key Skills

Education

Any Gradute