Why Join Us?

Why Join Us?

We are looking for a strong, hands-on Data Scientist to join our Data Loss Prevention team.

In this role, you will join an R&D team that researches, designs, and develops Check Point’s data loss prevention cloud services, providing state-of-the-art AI-based data loss prevention solutions on a global scale.

Check Point's data loss prevention solution is a platform used by all Check Point products, including Network Security, Email Security, SASE, Endpoint, SaaS, and Cloud Security.

In today's AI-driven world, data is an invaluable asset, and safeguarding it is paramount.

This role offers a unique opportunity to leverage extensive data collections and deliver transformative results in the Data Loss Prevention domain.

Key Responsibilities

• Join the research and development of new innovative capabilities for data loss prevention, involving advanced AI and algorithms.
• Quickly iterate on design approaches based on data-driven research and user feedback.
• Design and develop novel data-driven solutions that have the potential to deliver game-changing results involving advanced AI and algorithms.
• Utilize Natural Language Processing (NLP) and large language models to enhance data loss prevention capabilities.
• Work on web content categorization as part of the broader scope of data protection.
• Collaborate with Cyber Researchers, Analysts, Fellow programmers, and Data Scientists to deliver machine learning and analytics solutions.
• Push the solutions all the way to large-scale production systems. Understand the architectural constraints of such systems and work with a cross-organizational engineering and product team to quickly transition from prototype to a scalable robust implementation.
  
  

Qualifications

• At least 3-4 years of relevant experience and track record in Data Science: Machine Learning, Deep Learning, and Statistical Data Analysis.
• Proven experience in developing and deploying production-level models within enterprise environments.
• MSc or PhD degree in CS or Mathematics, Bioinformatics, Statistics, Engineering, Physics, or similar discipline.
• Strong hands-on experience in Python with a focus on statistical algorithms development.
• Experience with data science libraries such as: sklearn, pandas, numpy, pytorch/tensorflow.
• Team player, able to work in collaboration with subject matter experts, with the ability to clearly present and communicate findings.
• Proven ability to build and deliver data solutions in a short time frame.
• Experience with AWS, Docker, and development methodologies - an advantage.
• Active Github, Kaggle member – an advantage.
• Background in data loss prevention or related fields – an advantage.