Network Data Scientist: ML & Reliability

Description:

Exp - - Years

Role Overview
We are seeking a highly skilled Data Scientist with strong networking domain expertise to drive data-driven insights across network infrastructure, performance, and security. This role blends advanced analytics, machine learning, and network engineering knowledge to optimize network operations, improve reliability, and support next-generation networking solutions.
Key Responsibilities

• Analyze large-scale network data (logs, telemetry, traffic flows) to identify patterns, anomalies, and performance issues
• Develop and deploy machine learning models for network optimization, anomaly detection, and predictive maintenance
• Collaborate with network engineering teams to improve network design, capacity planning, and traffic routing
• Build data pipelines and scalable solutions for real-time and batch network data processing
• Design dashboards and visualization tools to monitor network health and KPIs
• Communicate findings and recommendations to both technical and non-technical stakeholders

• Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or related field
• + years of experience in Data Science / Machine Learning roles
• Strong programming skills in Python or R
• Hands-on experience with ML frameworks (, Tensor Flow, PyTorch, Scikit-learn)
• Solid understanding of networking concepts (TCP/IP, routing, switching, DNS, BGP, etc.)
• Experience working with large datasets using SQL, Spark, or Hadoop
• Strong problem-solving and analytical skills

• Experience in network telemetry, SDN (Software-Defined Networking), or cloud networking (AWS, Azure, GCP)
• Familiarity with network monitoring tools (Wireshark, Net Flow, SNMP, etc.)
• Knowledge of cybersecurity concepts and network threat detection
• Experience with real-time streaming tools (Kafka, Flink)
• Exposure to Dev Ops/MLOps practices

• Machine Learning & Statistical Modeling
• Network Analytics & Performance Optimization
• Data Engineering & Big Data Technologies
• Network Security & Anomaly Detection
• Data Visualization & Communication