Daniel Perez
About Daniel Perez
Daniel Perez serves as the Principal Technologist at Black Cape, where he develops custom mission applications and advanced data analytics for government defense projects. He holds a Bachelor of Science in Physics: Space Sciences from The University of Texas at Austin and a Master of Science in Computer Science from Georgia Institute of Technology.
Current Role at Black Cape
Daniel Perez serves as Principal Technologist at Black Cape since 2020. In this role, he develops custom mission applications and utilizes innovative data analytics to support government efforts in interpreting complex defense data. He also manages the internship and mentoring program for aspiring software developers, fostering the next generation of talent in the tech industry.
Education and Expertise
Daniel Perez holds a Bachelor of Science in Physics: Space Sciences from The University of Texas at Austin, where he studied from 2010 to 2014. He later earned a Master of Science in Computer Science from the Georgia Institute of Technology, completing his studies from 2019 to 2022. His educational background equips him with a strong foundation in both physics and computer science, enhancing his technical capabilities in data analytics and software development.
Professional Experience
Prior to his current position at Black Cape, Daniel Perez worked as a Software Engineer at Maxar Technologies from 2015 to 2020, where he contributed to various projects in the Austin, Texas area. He also held a Software Engineer role at Mitratech Holdings, Inc. from 2014 to 2015. Earlier in his career, he gained experience as a Research Assistant in the Astronomy Department at The University of Texas at Austin and as a Teaching Assistant for the Duke University Talent Identification Program.
Key Projects and Contributions
Daniel Perez has led significant projects throughout his career, including the design and development of a scalable ETL pipeline capable of processing millions of curated news articles and documents. This project incorporated natural language processing, machine learning, and topic modeling. He also developed an electronic medical record capturing system aimed at enhancing cancer research through modern and scalable design.