Erol Sirimoglu
About Erol Sirimoglu
Erol Sirimoglu is a Senior Systems Analyst/Programmer at Random House with over three decades of experience in systems analysis and programming.
Current Role at Random House
Erol Sirimoglu serves as a Senior Systems Analyst/Programmer at Random House. In this role, he has been managing a production data warehouse since 1990. His responsibilities include designing and programming decision support systems, as well as creating ad-hoc and urgent applications as necessary. His extensive experience in the field ensures the reliability and efficiency of mission-critical systems at Random House.
Previous Experience at Credit Suisse
Erol Sirimoglu spent two years at Credit Suisse, from 1988 to 1990, working initially as a support technician before transitioning into a programmer role. During his time at the company, he would have been involved in various technical support and programming tasks, contributing to the maintenance and development of financial systems.
Early Career at AIG
From 1987 to 1988, Erol Sirimoglu worked at AIG as a Tech Support/LAN installation technician. This early career role involved providing technical support and handling local area network (LAN) installations. The experience gained in this position laid the foundation for his subsequent roles in more complex technical and programming environments.
Education and Background
Erol Sirimoglu studied at Boston University, where he completed a Bachelor of Arts in Computer Science and Japanese from 1983 to 1986. His education provided him with a strong foundation in computer science principles and programming, which he has applied throughout his extensive career in systems analysis and programming.
Specialization in Data Modeling and Economic Theory
With over three decades of experience, Erol Sirimoglu specializes in data modeling and economic theory. His expertise in these areas enables him to design and create effective decision support systems and applications that meet the dynamic needs of his organization. His specialization ensures that data is accurately modeled and utilized for economic analysis.