Our Enterprise Information Services provide modern solutions to deliver a secure and scalable infrastructure.

Successfully deploying and maintaining a high-quality technology infrastructure is a high-risk endeavor. Government agencies and private industry require increasing levels of access to a suite of rapidly changing technologies. Failure to provide these end user services inhibits an organization’s ability to successfully meet mission requirements and degrades customer confidence in the ability to execute.

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We are innovating today to solve tomorrow's biggest challenges.

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Capability Highlights

Within the COLSA Data Science Lab we focus on the art of the possible in Machine Learning, Data Science, and AI. Innovation backed with experience armed with raw computational power to see ideas through.

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Want to join our team?

Join our expanding Data Science team and work to innovate the future alongside other pioneers of the industry.

Meet a few of our industry-leading experts.

Jay Sebastian

Senior Data Scientist

Jay is a Senior Data Scientist and Program Manager at COLSA. He joined COLSA in 2019, with over 20 years of leadership experience in Strategic Planning, Project and Program Management, Information Technology, Business Development, Data Science/Artificial Intelligence research and business growth, and Information Assurance. He is driven by the challenges in solving complex problems across multiple domains leveraging recent advances in technology, building business opportunities, and leading teams of the best and brightest data science and AI practitioners.

Jay earned a Bachelor of Science in Computer Science from the United States Naval Academy and a Master of Science in Computer Science from The George Washington University. His current areas of research include Trusted and Ethical AI, Knowledge Graphs and Graph Theory, and Scientific Machine Learning (SciML).

Dr. Rachel Lucas

Data Scientist

Rachel is a Data Scientist at COLSA. She joined the company recently and is passionate about solving impactful and unique problems at the intersection of data science and scientific fields such as physics. Rachel earned a B.S. in Aerospace Engineering and a B.S. in Applied Physics from Purdue University and recently graduated from the University of California, Irvine where she earned her PhD in Physics.

While earning her doctorate, her area of research was in the nano-regime and she is looking forward to applying the knowledge gained throughout her education to emerging areas of artificial intelligence such as Scientific Machine Learning (SciML).