Description

We are looking for a strong, hands-on Security Researcher with knowledge in Data Science to join a cutting-edge AI and cyber security initiative at Check Point.

In this role, you’ll be part of a growing data science team working on advanced prevention technologies, leveraging vast amounts of data and state-of-the-art machine learning techniques to help protect users on a global scale.

This is a unique opportunity to join a high-impact, research-driven environment, where you will have the chance to shape core components of a next-generation security solution.

Major Responsibilities

• Research and develop innovative AI-powered capabilities for cyber threat prevention.
• Perform hands-on malware analysis in Windows environments, focusing on files and related threats.
• Rapidly prototype and iterate based on data insights and user feedback.
• Design and build data-driven solutions with a strong emphasis on practical impact and performance.
• Collaborate closely with cyber researchers, analysts, and engineers to deliver production-grade machine learning models.
• Work across organizational boundaries to bring solutions from concept to large-scale deployment, considering system constraints and integration challenges.

Desired Background

• BSc in Computer Science, Mathematics, Bioinformatics, Statistics, Engineering, Physics, or a similar discipline; MSc is an advantage.
• At least 2 years of hands-on malware analysis experience in Windows environments, focusing on file-based threats - must
• At least 2+ years of experience applying data science techniques, including Machine Learning, Deep Learning, and statistical data analysis, with practical hands-on work in Python.
• Comfortable using data science libraries such as: sklearn, pandas, numpy, pytorch,langchain with a focus on developing statistical and machine learning algorithms.
• At least 2 years of experience using AI tools in practical applications.
• Team player, able to work in collaboration with subject matter experts, with the ability to present and communicate findings.
• Proven ability to build and deliver data solutions in a short time frame.

Advantages

• Experience with AWS, Docker, and development methodologies.
• Experience with Databricks.
• Knowledge in AI edge technologies such as MCP and automated analysis tools such as langflow, n8n etc.