Senior Data Scientist
Role details
Job location
Tech stack
Job description
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 Collaboration & Operations Support Work closely with NOC, Network Engineering, and Reliability teams Translate analytical findings into operational recommendations Support proactive maintenance and incident prevention initiatives Visualization & Reporting Create interactive dashboards and reports for real-time fault monitoring Present insights clearly to technical and non-technical stakeholders
Requirements
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, Strong analytical and problem-solving skills Ability to communicate insights effectively Experience working in cross-functional operational teams Desired Skills Python | Data scientist
