Tech Stack

Description

You will investigate how modern networks behave at scale, diving into protocols, traffic patterns, and path performance to design data-driven improvements that enhance reliability, efficiency, and user experience across Cato's global network. You'll develop analysis tooling, run large-scale measurements, and share findings.

Requirements

• BSc + MSc in Computer Science
• Strong foundations in computer networking and Internet protocols (TCP/IP, QUIC/HTTP/3, HTTP/2, DNS, RDP, DHCP, routing, MPLS, NAT, load balancing)
• Proficiency in Python, Go, or Java and solid SQL skills
• Experience with big-data platforms (e.g., Spark) and databases (Elasticsearch, MongoDB, MySQL, AWS Athena)
• Practical experience applying machine learning to network data (pandas, NumPy, scikit-learn; familiarity with PyTorch)

Responsibilities

• Build analysis tools, datasets, and reproducible pipelines for research at scale
• Perform deep protocol analysis (TCP, QUIC/HTTP/3, HTTP/2, DNS, DHCP) including edge cases and performance aspects
• Analyze latency, jitter, loss, throughput, and path selection; build models and KPIs
• Design controlled experiments and A/B tests; validate findings on real traffic
• Translate research into product improvements with clear specs and reference implementations