Staff Security Researcher

• Conduct original security research to identify emerging identity attack vectors and develop novel detection methodologies
• Design and implement advanced analytics including rule-based systems, behavioral analysis, and machine learning models for threat detection
• Expand and optimize our large-scale entitlement graph systems that map privilege escalation paths across customer environments
• Develop proactive recommendation engines that identify security misconfigurations before they become attack vectors

• Build production-grade security systems with emphasis on scalability, reliability, and performance optimization
• Implement and maintain detection pipelines using PySpark, Spark SQL, and distributed computing frameworks
• Design custom data representations (graphs, time-series, etc.) to support advanced analytical capabilities
• Establish engineering best practices including comprehensive unit testing, automation, and CI/CD pipelines

• Explore large-scale customer datasets using Spark and Databricks to validate detection hypotheses and uncover new threat patterns
• Continuously monitor and tune detection algorithms based on real-world telemetry and performance metrics
• Collaborate with data science teams to integrate machine learning models into production detection systems
• Optimize system performance to handle massive data volumes efficiently

• Provide technical leadership and mentorship to product and engineering teams
• Present research findings at industry conferences and security forums
• Publish technical blogs and research papers to establish thought leadership
• Collaborate with cross-functional teams to translate research insights into product roadmap priorities

• Strong engineering background with proven experience developing and maintaining production security systems
• Strong Python programming skills with experience in large-scale data processing
• Proficiency in SQL and database optimization techniques
• Experience working with SIEM tools, log analysis platforms, or similar security data systems
• Knowledge of adversarial tactics, techniques, and procedures (TTPs) and corresponding defensive strategies
• Experience in engineering event detection and response systems with focus on tuning and optimization

• Big data processing experience with Apache Spark, Databricks, or similar distributed computing platforms
• Background in security research with published findings or conference presentations
• Knowledge of cloud security, containerization, and modern infrastructure technologies
• Experience with graph databases and network analysis techniques
• Familiarity with machine learning applications in cybersecurity
• Track record of speaking at technical conferences or contributing to security research publications

• Python
• SQL and database technologies
• Distributed data processing frameworks

• Apache Spark / PySpark
• Databricks platform
• Graph databases and analysis tools
• Cloud platforms (AWS, Azure, GCP)
• Containerization technologies (Docker, Kubernetes)
• Machine learning frameworks and libraries

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