Description

You will build data pipelines and machine learning models for 5G wireless network alarm analysis.

Responsibilities

• Design and automate data pipelines to clean, normalize, and enrich alarm data from OSS, EMS, NMS, and CMDB systems.
• Develop machine learning models for alarm correlation, noise reduction, and root cause analysis using supervised and unsupervised techniques.
• Implement anomaly detection and predictive fault forecasting for RAN and Core network domains.
• Analyze large-scale network alarm data to identify patterns, trends, and recurring fault signatures.
• Create KPIs and dashboards to monitor network health and fault trends.

Required Skills

• 5+ years of experience in data engineering and machine learning.
• Strong hands-on experience with PySpark and Apache Flink for large-scale data processing and streaming.
• Proficient in Python for Data Science.
• Expertise in machine learning modeling, including clustering, classification, and time-series analysis.
• Solid understanding of 5G Wireless Networks (RAN/Core) and network alarm data sources.
• Experience integrating data from OSS, NMS, EMS, and CMDB systems.
• Bachelor's degree in a relevant technical field.

Key Skills

Education

Bachelor's degree