Michael Frank
About Michael Frank
Michael Frank is an IT Support Technician at Core BTS in Glen Cove, New York, with over 15 years of experience in troubleshooting computer hardware and software issues. He has a background in Mechanical Engineering from New York University and has developed skills in various web technologies and design tools through self-study.
Work at Core BTS
Michael Frank has been employed at Core BTS as an IT Support Technician since 2021. In this role, he is responsible for troubleshooting computer hardware and software issues within a Windows network environment. His position requires him to participate in a revolving on-call schedule, providing 24/7 support to users. This commitment highlights his dedication to user support and effective problem resolution.
Previous Employment Experience
Prior to his current role, Michael worked at FJC Security Services, Inc. as an IT Technician from 2014 to 2016. He also held a brief position at Robert Half Technology in 2014, where he was involved in IP Phone Deployment for one month. His diverse experience in IT roles has contributed to his extensive knowledge in the field.
Education and Expertise
Michael Frank holds a Bachelor of Science degree in Mechanical Engineering from New York University - Polytechnic School of Engineering, which he completed from 1994 to 1998. He further enhanced his technical skills through online courses on platforms such as Coursera and Udemy, studying subjects including Web Design, Git/GitHub, Principles of Graphic Design, Modern CSS Workflow, and JavaScript from 2016 to 2017.
Technical Skills and Proficiencies
With over 15 years of experience in troubleshooting computer hardware and software issues, Michael has developed a strong proficiency in managing user accounts via Active Directory. He is skilled in documenting issues within various helpdesk ticketing systems, ensuring efficient tracking and resolution of technical problems. Additionally, he has self-taught skills in Photoshop, Illustrator, HTML, and CSS, acquired through independent learning methods.