Scalence L.L.C. · 2 days ago
Data Scientist - Network Fault Management (Wireless & IEN Alarms)
Basking Ridge, NJ
Full-time
Onsite
Mid LevelScalence L.L.C. is seeking a Data Scientist specializing in Network Fault Management. The role involves analyzing large-scale wireless network alarm data, developing machine learning models, and collaborating with cross-functional teams to enhance network reliability and proactive maintenance.
Information Technology & Services
Responsibilities
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
Build machine learning models for alarm correlation, noise reduction, root cause analysis, anomaly detection, and predictive fault forecasting
Apply supervised and unsupervised learning techniques such as clustering, classification, and time-series analysis
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
Collaborate with NOC, Network Engineering, and Reliability teams to translate analytical findings into operational recommendations
Support proactive maintenance and incident prevention initiatives
Create interactive dashboards and reports for real-time fault monitoring
Present insights clearly to technical and non-technical stakeholders
Deliverables include alarm correlation and RCA models reducing false positives, predictive fault alerts improving proactive maintenance, operational dashboards for NOC and engineering teams, and documentation with model performance reports
Qualification
Required
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
Build machine learning models for alarm correlation, noise reduction, root cause analysis, anomaly detection, and predictive fault forecasting
Apply supervised and unsupervised learning techniques such as clustering, classification, and time-series analysis
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
Collaborate with NOC, Network Engineering, and Reliability teams to translate analytical findings into operational recommendations
Support proactive maintenance and incident prevention initiatives
Create interactive dashboards and reports for real-time fault monitoring
Present insights clearly to technical and non-technical stakeholders
Strong proficiency in Python or R (Pandas, NumPy, Scikit-learn, PySpark)
Experience with time-series data and event/alarm analytics
Knowledge of machine learning algorithms for classification, clustering, and anomaly detection
Experience with SQL and big data platforms such as Spark or Hadoop
Familiarity with visualization tools like Tableau, Power BI, Grafana, or Python visualization libraries
Understanding of wireless networks (2G/3G/4G/5G, RAN, Core)
Knowledge of IEN/IP/Ethernet networking concepts
Familiarity with network alarms, fault management, and OSS/NMS systems
Understanding of MTTR, SLA, availability, and reliability metrics
Strong analytical and problem-solving skills
Ability to communicate insights effectively and work in cross-functional operational teams
Preferred
Experience in telecom, ISP, or network operations environments
Knowledge of AIOps or network intelligence platforms
Experience with real-time streaming data tools such as Kafka or Flink
Exposure to ITIL and incident/problem management frameworks
Company
Scalence L.L.C.
In today’s dynamic and competitive market, success hinges on mastering three key areas: Data Intelligence, Business Resilience, and Digital Experience.
501-1000 employees
Funding
Current Stage
Late StageCompany data provided by crunchbase