Pedro Atanásio
About Pedro Atanásio
Pedro Atanásio is a Staff Software Engineer at Incognia, specializing in creating anonymous location behavioral patterns for mobile applications. He has extensive experience in software engineering, having worked at various companies in Brazil since 2010.
Work at Incognia
Pedro Atanásio currently holds the position of Staff Software Engineer at Incognia, a role he has occupied since 2021. In this capacity, he specializes in creating anonymous location behavioral patterns for mobile applications by utilizing network signals and on-device sensors. His work focuses on providing location context and developing private identities for users, which enhances ID verification and fraud detection. Prior to his current role, he worked as an Engenheiro de Software at Incognia from 2017 to 2021, contributing significantly to the company's anti-fraud solutions.
Previous Experience
Before joining Incognia, Pedro Atanásio gained valuable experience in various roles. He worked at FRT Tecnologia Eletrônica as an Estagiário de Desenvolvimento de Software Embarcado from 2011 to 2012 and later as an Engenheiro de Software from 2013 to 2017. He also served as a Desenvolvedor at GPRT/UFPE for four months in 2013. His early career included a position as an Instrutor (C/C++) at Centro Integrado de Tecnologia da Informação in 2010 and as an Estagiário de Suporte de TI at Tribunal Regional Federal da 5ª Região in 2011.
Education and Expertise
Pedro Atanásio completed his high school education at Colégio Militar do Recife from 2000 to 2006. He then pursued a Bachelor's Degree in Engenharia da Computação at Universidade Federal de Pernambuco, graduating in 2012. His academic background laid the foundation for his expertise in developing location technology, particularly in creating private location awareness for connected devices. He has also contributed to the development of anti-fraud solutions that are significantly more precise than traditional GPS.
Specialization in Location Technology
Pedro Atanásio specializes in creating anonymous location behavioral patterns for mobile applications. His work involves leveraging network signals and on-device sensors to enhance user privacy while providing accurate location context. He focuses on developing solutions that improve ID verification and fraud detection processes, ensuring that users maintain their privacy while benefiting from location-based services. His contributions to Incognia's anti-fraud solutions demonstrate his commitment to advancing location technology.