Threat Classification Analyst

Summary

Data has never been more valuable and vulnerable. As cybercriminals become more sophisticated and regulations become stricter, organizations struggle to answer one key question: “Is my data safe?”

At Varonis, we see the world of cybersecurity differently. Instead of chasing threats, we believe that the most practical approach is to protect data from the inside out. We’ve building the industry’s first fully autonomous data security platform to help our customers dramatically reduce risk with minimal human effort.

At Varonis, we move fast. We’re an ultra-collaborative company with brilliant people who care deeply about the details. Together, we’re solving interesting and complex puzzles to keep the world’s data safe.

We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.

As a Threat Classification Analyst, you will be a key contributor in defending Varonis' customers from various threats including email-based threats. Through the meticulous categorization and classification of large volumes of data, your work will support the optimization of email threat-detection helping to accurately identify and differentiate between various types of emails including business email compromise (BEC) fraud, phishing attacks, malicious payloads, and spam.

Responsibilities

• Accurately label and categorize emails in large datasets, ensuring the quality and consistency of the data.
• Identify and classify different types of emails, including both malicious and legitimate communications.
• Assist in the maintenance of labelling guidelines, ensuring they are up-to-date and reflective of the latest email observations.
• Collaborate within the team, as well as with research and data science teams, to provide feedback and insights on email trends and patterns observed during the labelling process.
• Peer-review and validation of labelled datasets, ensuring they meet required standards.
• Develop and maintain knowledge about emerging email threat types, and general cybersecurity trends, to enhance labelling accuracy and relevance.
  
  

• Experience with data labelling, particularly in the context of AI/ML projects, is highly desirable.
• Strong attention to detail with the ability to accurately classify and categorize large volumes of data.
• Familiarity with different types of emails and email threats, including fraud, phishing, and spam.
• Basic understanding of email data structures, protocols, and technologies, in particular how these can be used to determine intent.
• Excellent organizational and time management skills, with the ability to manage multiple tasks simultaneously.
• Ability to work independently and as part of a team with strong communication skills, both written and verbal.
• Willingness and keen to develop email threat analysis and cybersecurity skills.