* Develop advanced machine learning models to identify high-risk business processes and users within a user base exceeding 30,000.* Led a pioneering project to architect and deploy a state-of-the-art cloud data lake, enabling aggregation, visualization, and in-depth analysis of over 50 distinct data feeds within the Data Security domain.* Partner with Data Loss Prevention (DLP) team to optimize detections and configurations for email, web, and endpoint* Streamline and automate data security workflows, seamlessly transitioning critical analytic processes to the cloud environment.* Collaborate with data security teams, contributing expertise to projects spanning machine learning integration, process automation, graph analysis, and the enhancement of security logging protocols.

* Course: Applying Machine Learning to Advance Cybersecurity* Pratt School of Engineering, Master of Engineering in Cybersecurity

* Offered expert consulting in analytics and security to senior leadership within government agencies.* Innovated and delivered tailored analytic resolutions to clientele, such as designing entity extraction systems and graph database tools that revealed duplicative expenses within the Department of Defense.* Contributed extensively to pre-sales activities, providing adept assistance in analytics and security for a multitude of industry-leading security providers including Palo Alto, ZScaler, Crowdstrike, Red Canary, SentinelOne, Netskope, Splunk, and numerous others.

* Directed a dynamic team comprising over 10 data scientists and security specialists.* Significantly enhanced threat hunting procedures by implementing AI-driven automations, resulting in a remarkable 90% reduction in manual alert aggregation and case creation.* Engineered robust streaming analytics functionalities within Spark Streaming, empowering the processing of volume exceeding 1 billion security logs daily.* Collaborated closely with ETL, development, and UI teams, ensuring the timely roll-out of novel product features based on prioritized requirements.

Acquired by Cybraics (2016)* Acquired technology led to $6 million ARR in first year of general availability at Cybraics* Startup focused on developing analytics for enterprise scale threat detection.* Built streaming architecture to ingest, analyze, and visualize data* Developed machine learning models to detect malicious behaviors for multi-terabyte network logs

* L3 Technology Fellow (less than 1% of employees awarded)* Led data science team for $500M Intelligence business unit (Multiple US intelligence agencies and dozens of projects)* Managed team of data scientists, software engineers, and subject matter experts

* Methods developed include artificial neural networks, social network analysis, natural language processing, and various data collections approaches* DARPA information security research* Led development of enterprise monitoring and advanced threat detection software* Experience with commercial and government clients building social media event detection and user behavior/segmentation models