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Tier-1 brand and remote pan-India reach balanced by niche telecom AIOps specialization reducing generic applicant density.
Role requires telecom network analytics, TMF SID, and AIOps domain expertise, limiting cross-industry transferability.
Explicit 6–12 years plus many mandatory ML, telecom, and data engineering skills increases filtering stringency.
Analyze telecom network data across multiple domains including RAN, Core, IP, Transport, and Cloud to develop KPI and ML models for performance, fault prediction, and anomaly detection.
Build and maintain data pipelines for feature engineering and support advanced analytics such as digital twin, graph analytics, and AIOps use cases including alarm reduction and predictive maintenance.
Collaborate with AI/LLM teams to provide datasets and align network data models with industry standards (TMF SID/Open API) to enable AI agents and RAG applications.
6 to 12 years of relevant work experience in AI/Data Science related to telecom network analytics.
Proficiency in Python, Statistics, Machine Learning, KPI & Feature Engineering, Network Performance Analytics, Fault Analysis, and AIOps techniques.
Experience with data pipeline development and quality management, Graph Analytics, Digital Twin analytics, TMF SID/Open APIs, and platforms like BigQuery or equivalents.
Notice Period: Immediate to 60 days; Location: PAN India.
Experienced in telecom network domains including RAN, Core, IP, SD-WAN, and Transport with hands-on analytics and ML modeling for network performance and fault management.
Skilled in integrating AI/LLM technologies with network data and familiar with industry data modeling standards to support AI-driven operations.
Capable of designing scalable data pipelines and advanced analytics frameworks like digital twin and graph analytics to drive proactive network assurance and AIOps solutions.