Data Analyst

A high-profile Web3 Security pioneer and a global category leader, backed by the world’s most prestigious Venture Capital funds and global tech giants.

The company is architecting the essential "trust layer" for the decentralized economy, providing mission-critical protection for the industry's most prominent platforms including the world’s leading digital wallets and high-scale crypto infrastructures.

By securing the ecosystem for industry giants and ventures led by world-class AI pioneers, the organization is removing the final barriers to global blockchain adoption.

Located in a prime Tel Aviv tech hub with excellent transit accessibility, the company fosters an elite, high-intensity, in-office R&D culture dedicated to solving the most complex challenges in digital asset protection.

The Role & Responsibilities-

• Advanced Forensic Research: Leading deep-dive investigations into massive data pipelines to identify emerging attack vectors and sophisticated fraud patterns.
• Pattern Recognition & Inference: Designing and executing complex queries and scripts using Python and SQL to extract actionable security insights from decentralized networks.
• Data-Driven Product Influence: Translating research conclusions into strategic trends that directly shape the product’s core detection engines and logic.
• Trend Analysis: Identifying systemic shifts in the security landscape, ensuring the platform stays ahead of global cyber-threats.
• Collaborative R&D: Working at the intersection of Data Science, Security Research, and Backend Engineering to build a resilient digital economy.

Requirements-

• Analytical Seniority: Significant professional experience as a Data Analyst or Information Security Analyst – Mandatory.
• Security DNA: Proven professional background within the Cyber-Security industry – Mandatory.
• Technical Mastery: Expert-level proficiency in SQL and solid development experience in Python – Mandatory.
• Forensic/Research Skills: Strong capability for investigative research and the ability to draw conclusions from complex, non-structured data environments.