Data Analyst- Part time

1 week ago

Herzliya, Tel Aviv, Israel Varonis Full time ₪60,000 - ₪80,000 per year
Summary

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

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 Research & Pattern Definition
  • 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.

Required Qualifications:
  • 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.

Preferred Qualifications:
  • 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.

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