Senior Data Science Engineer – Telecom(NCS/Job/ 1596)

We are hiring a Senior Data Science Engineer to design scalable data science pipelines and build robust machine learning models that drive business outcomes and to build data-driven solutions for telecom network operations, customer analytics, and predictive maintenance. The candidate should handle large-scale time series and log data for anomaly detection and performance optimization.

Key Responsibilities:

• Build, test, and optimize machine learning models using structured and unstructured data.
• Build predictive models for network outage detection, churn, and SLA violations.
• Develop data pipelines that consume OSS/BSS data, CDRs, and network KPIs.
• Apply time series models (ARIMA, Prophet) and ML algorithms for fault prediction.
• Optimize network parameters using AI/ML and statistical models.
• Collaborate with network analytics, RF, and operations teams.

Requirements:

• Strong data wrangling with telecom formats (CSV, JSON, SNMP, NetFlow).
• Strong in Python, Pandas, NumPy, SQL, and Scikit-learn.
• Experience with ML model lifecycle tools (MLflow, Airflow, Kubeflow).
• Deep understanding of supervised, unsupervised, and time series modeling.
• Familiar with telecom tools/data sources: Zabbix, Nagios, CEM, NetAct, ENM.
• Understanding of 4G/5G architecture, OSS/BSS, and KPI monitoring.