Mr. Thomas is a senior data scientist and cyber security architect with Legal Analysis Systems. His principal responsibilities at LAS include processing data supporting asbestos litigation claims for large bankruptcies and trusts, ensuring the confidentiality, integrity and availability of that data to the LAS team, and securing the data of LAS clients using a combination of cloud computing services and secure analytic services.

Mr. Thomas has over 30 years' experience architecting and deploying robust analytic support systems, including relational and NoSQL data storage platforms. He has spent the last 10 years applying progressively-automated means to clean, process, analyze, and visualize complex data.  

Mr. Thomas’ expertise has most recently focused on applying supervised and unsupervised machine learning techniques such as natural language processing, clustering, novelty and outlier identification, as well as image and object recognition, to streamline the analysis of liability claims information from unstructured documents, achieving highly accurate document classification.  He also uses similar techniques to find patterns and anomalies in claims data—both to support estimations and predictions, and to standardize millions of records containing varying forms of exposure and occupational information. 

Mr. Thomas developed many of his methods as the Chief Architect and Chief Information Security Officer at RAND Corporation, where he reported to the CIO and was responsible for developing data management and processing standards, and most recently delivery of zero-trust architecture initiatives.

He loves everything about oceans, including visiting coastal cities around the world and enjoying sailing, paddle boarding, snorkeling and swimming between Marina Del Rey and Catalina Island in California, and anywhere else he gets the opportunity.

Email him at cord.thomas (at) legalstat.com.