Cyber security data scientist focusing on network intrusion detection and insider threat identification through custom-built machine learning models.

Project manager of 7-person team that oversaw the health of a 3-environment, 17-server platform. Typical duties included managing database performance, security, network performance, business intelligence tool performance, software upgrades, and application license management. Also led a team of 5 engineers to migrate a mission-critical, production-grade, on-prem infrastructure to AWS cloud (SC2S) that is used by a potential 50,000 users. Designed and programmed machine learning models in both unsupervised and supervised methods. Built unsupervised text analytics machine learning model to cluster survey data from open text forms resulting in discovering of new information not found in structured form fields. Also allowed for the discovery of unknown linked events throughout suspicious activity reports. Built supervised text analytics machine learning model to match new hires to best-fit project openings. Used existing hired staff and corresponding resumes to train a model to predict best fit of resumes to positions. Also built unsupervised machine learning topic modeling products to categorize events from various text sources.

Led multiple data analytics projects to support the client’s goal of making better decisions based on data trends, which included interviews of data owners and stakeholders.

Assigned to the Project Management Office team reporting to the Managing Partner and Managing Director to oversee contractual and financial performance of a five-year $500M contract with 450+ employees.