Jay Meil
Chief Data Scientist and Managing Director of Artificial Intelligence
SAIC
Jason “Jay” Meil is the director of data science and chief data scientist for SAIC’s Artificial Intelligence (AI) Innovation Factory, where he leads AI technical strategy and solutions that enable rapid decision-making at scale in support of multiple intelligence disciplines.
With two decades of experience in applied mathematics, data science and deep learning, Meil is a recognized expert in analytical tradecraft, all source intelligence and open source intelligence. He serves as a technical advisor to numerous intelligence organizations within the Intelligence Community (IC) and Department of Defense (DOD), applying his tradecraft to the domains of intelligence, surveillance and reconnaissance; targeting; and algorithmic warfare.
Meil has led cross-functional teams in designing, building and deploying deep learning models to support federal government customers in complex missions of national importance, with the ultimate objective of making the nation safe against peer and near-pear threats. In addition to IC and DOD customers, he has supported civilian agencies including the Department of Homeland Security.
As an SAIC research fellow, Meil has focused on two areas:
integrating multi-modal intelligent decision support systems into command and control operations
offensive and defensive AI algorithms in identity intelligence, information warfare, information operations and unconventional warfare (I2/IW/IO/UW) operations.
Meil is a frequent participant in research panels and industry discussions on the impact of AI on national security, including with the John Hopkins University Applied Physics Laboratory; the Center for Security in Politics at UC-Berkeley on behalf of DARPA; CERN’s OpenLab and Quantum Technology Initiative; the European Geosciences Union; the Atlantic Council Scowcroft Center for Strategy and Security; the Potomac Officers Club; and AFCEA.
Meil, who is committed to lifelong learning, has numerous academic credentials in computer science, data science and AI. He has completed a MicroMasters from MIT in data, economics and development policy. He has certifications in quantitative analytics from the Wharton School (Aretsy School of Executive Education) and applied mathematics for deep learning from Imperial College of London. He holds certifications as a senior data scientist from the Data Science Council of America and data analytics from Six Sigma Global Institute. He has completed a 9-month intensive fellowship in data science and machine learning with Lambda Institute.