Summary

Data has never been more valuable and vulnerable. As cybercriminals become more sophisticated and regulations more strict, 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 the most practical approach is protecting data from the inside out. We’ve built 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.

This is a part time job (70%)

Job Overview, Key Responsibilities:

Data Analysis & Validation

• Data Collection & Preparation: Gather and clean datasets, ensuring high data quality and integrity.
• Root Cause Analysis: Investigate anomalies and classification errors to uncover underlying issues.
• Business Translation: Collaborate with product managers to translate business needs into data insights and classification logic.
• Model Evaluation & Metrics: Evaluate classification accuracy using pivot tables, statistical metrics (accuracy, precision, recall), and manual review.
• Validation Reporting: Document validation results, highlight discrepancies, and communicate findings clearly to stakeholders.
• Continuous Improvement: Analyze false positives/negatives to refine detection logic and enhance model performance.
  
  

• Regulatory Analysis: Research and interpret standards (e.g., HIPAA, GDPR, PCI DSS) to define detection patterns.
• Regex & Pattern Engineering: Develop and maintain regular expressions and pattern-matching logic for entity detection.
• Validation Support: Cross-verify data against regulatory patterns using automated tools and manual inspection.
  
  

• Advanced Excel Skills: Expertise in pivot tables, conditional formatting, macros, VLOOKUP/XLOOKUP, and data validation.
• Attention to Detail: Strong ability to detect inconsistencies in large datasets and track validation decisions.
• Documentation Literacy: Skilled in following and contributing to structured documentation and validation protocols.
• Analytical Thinking: Creative and strategic problem-solving with a focus on continuous improvement.
  
  

• Education: Background in Statistics, Information Systems, Computer Science, Mathematics, Linguistics, Physics, or related analytical fields.
• Domain Experience: Background in data analysis, classification, machine learning, or compliance-driven environments.
• LLM Familiarity: Understanding of large language models, their classification logic, and output interpretation.
• Industry Familiarity: Experience in SaaS or cybersecurity, with knowledge of encryption, data security, and compliance standards (e.g., GDPR, CCPA).
• Regex Proficiency: Hands-on experience with regular expressions and pattern recognition.