Network Data Scientist - Spring boot, React JS, Node JS

Title: Network Data Scientist - Spring boot, React JS, Node JS

Location: Basking Ridge, NJ

Salary Range: $51/hr

Introduction

Join our dynamic team to analyze and optimize large-scale wireless and network alarm data. We are seeking a skilled professional to develop machine learning models and create insightful dashboards to enhance network fault management. Your work will directly impact the reliability and efficiency of our network operations.

Required Skills & Qualifications

Applicants must be able to work directly for Artech on W2

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

Must have 7+ years of experience in Node.js

Must have 7+ years of experience in React.js

Must have 7+ years of experience in Spring Boot

Strong analytical and problem-solving skills

Ability to communicate insights effectively and work in cross-functional operational teams

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

Day-to-Day Responsibilities

Analyze large-scale wireless 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

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

For immediate consideration please click APPLY to begin the screening process with Alex.