Data Scientist

Welcome to the future of cloud networking and security!

Cato Networks is the first company to converge enterprise networking and security into one centralized and global service that is delivered by cloud. It is led by networking and security pioneer Shlomo Kramer (Check Point, Imperva) and early investor (Palo Alto Networks, Exabeam, Trusteer and more). Cato's unique technology inspired a brand-new product category, later named "SASE" by Gartner and a market expected to reach $28.5 billion by 2028.

This is your opportunity to get on the rocket ship and join a company that is building a cutting-edge enterprise network and secure cloud platform, and is on a fast track to becoming the worldwide market leader – don't miss it!

Data Scientist position

We are looking for a talented and experienced Data Scientist to join our Research Data Science team and play a key role in shaping the future of cloud-native network security. Your primary mission will be to lead the development and deployment of AI-driven capabilities that protect enterprise networks at scale through Cato's SASE platform, powering core products such as our AI assitant, DLP, XDR, IPS, and more.
Leveraging rich, real-time data from our global backbone and Cloud data warehouse, you will apply advanced reserach analytics, machine learning, deep learning and GenAI techniques to solve complex cybersecurity and networking challenges.

This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.

Key Responsibilities

Lead the design, development, and deployment of AI/ML models that enhance Cato's security and networking products
Leading networking and security research, including analysis of large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
Research, fine-tune, and train models optimized for real-time inline inference under limited compute resources
Collaborate cross-functionally with product, engineering, and support teams to translate product and business needs into AI solutions
Define and track success metrics to ensure AI solutions meet performance and business goals

Qualifications

Minimum 3 years of professional experience in Data Science roles
Hands-on experience in networking and/or cybersecurity domains
Proven experience building and deploying LLM-based applications and agents (e.g., RAG pipelines, tool-use agents, prompt engineering at scale)
Strong foundation in classical machine learning methods (supervised, unsupervised learning, clustering)
Practical experience with deep learning frameworks such as TensorFlow or PyTorch, including NLP techniques
Proven experience deploying models on cloud platforms like AWS, Azure, or Google Cloud
Excellent analytical, problem-solving, and communication skills
Self-motivated, collaborative, and able to work independently

How to Stand Out

Experience with real-time or low-latency AI inference in production environments.
Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field