Cybersecurity work is grounded in applied data science and systems engineering, focused on understanding, analyzing, and improving large-scale security platforms operating in production environments.

Experience spans multiple layers of modern security systems, including web application protection, exposure management, asset discovery, and vulnerability analysis. A significant part of this work involves applying machine learning, statistical analysis, and data-driven reasoning to security problems such as intelligent bot detection, risk scoring, and prioritization of security signals at scale.

Rather than treating security as a collection of isolated tools, the work emphasizes system-level understanding: how data flows through security platforms, where bottlenecks and blind spots emerge, and how security systems can be optimized, observed, and evolved over time to support informed decision-making and effective protection.