Data Analyst

DLP's rule-based framework is broken. We asked machines to find problems with rigid rules, then expected humans to investigate the noise - an impossible task. Jazz is the new model. It starts with total coverage from a forensic endpoint agent and uses a powerful Agentic Investigator that learns your business. It delivers clear, pre-investigated answers instead of alerts, and is designed to be run by a single person. Finally, DLP that works.

Founded in 2024 and backed by leading cybersecurity investors, Jazz is already deployed with customers worldwide and scaling fast.

We are looking for a Data Analyst to serve as the human-in-the-loop for our AI detection systems. In this role, you will validate and enrich AI-generated outputs, investigate model behavior, and help improve the accuracy and reliability of our threat detection engine. Your work will directly influence how the system learns, adapts, and performs in production environments.

What You’ll Do

• Play a critical role in shaping how our AI investigates security risks by improving the system's accuracy, reliability, and real-world effectiveness.
• Review and analyze outputs from our AI threat detection engine to ensure high-quality, reliable security insights.
• Investigate security alerts and validate classifications to uncover weaknesses in model behavior and detection logic.
• Identify patterns behind false positives and false negatives, perform root cause analysis, and drive improvements to model accuracy.
• Work closely with AI engineers to refine detection logic, strengthen feedback loops, and continuously improve model performance.
• Monitor production signals, including precision, recall, false-positive rate, model drift, and latency, to ensure the system performs reliably at scale.
• Surface meaningful insights from model behavior and translate them into clear, actionable improvements for engineering.
  
  

• 3+ years of experience as a Data Analyst in a fast-paced cybersecurity startup, working with large-scale security data and rapidly evolving systems.
• Strong analytical skills with experience evaluating complex data and performing root cause analysis.
• Ability to communicate findings clearly and translate analysis into actionable insights.
• Familiarity with Python or scripting used for data analysis and annotation workflows.
• Understanding of large language models and key parameters such as temperature, top-p, system prompts, and context windows.
• Curiosity and attention to detail when investigating anomalies, model behavior, and detection outcomes.
• Ability to collaborate closely with engineering and AI teams in a fast-moving environment.
  
  

• Work on real-world AI systems that power a new approach to Data Loss Prevention.
• Play a critical role in improving the accuracy and reliability of AI-driven threat detection.
• Collaborate closely with AI engineers and security experts on complex cybersecurity challenges.
• Join an early-stage company where your insights directly influence product quality and model performance.
• Be part of a team building the next generation of AI-powered security systems.