Waseem Akhtar
About Waseem Akhtar
Waseem Akhtar is a Senior Java Developer with extensive experience in application architecture and module development. He has worked at Alivia Technology since 2014 and previously at CABIDZ from 2017 to 2019, contributing to various projects including 'Redline Pre-Trade Risk' and 'Absolute Insight'.
Work at Alivia Technology
Waseem Akhtar has been employed at Alivia Technology as a Senior Java Developer since 2014. His role involves designing application architecture and developing modules and services for various projects within the company. His contributions have been integral to the development of applications that leverage advanced technologies.
Previous Experience at CABIDZ
Prior to his current role, Waseem Akhtar worked at CABIDZ as a Java Software Developer from 2017 to 2019. During his two years in Sydney, Australia, he focused on software development and contributed to various projects that enhanced the company's technological capabilities.
Education and Expertise
Waseem Akhtar earned a Bachelor of Science in Information Technology (BSIT) from Islamia University, Bahawalpur, where he studied Computer Programming and Software Engineering from 2009 to 2013. He also completed his Pre-Engineering studies at Government Sadiq Egerton College, Bahawalpur, from 2006 to 2009, and attended Govt. Abbasia Higher Secondary School from 2004 to 2006.
Key Projects and Contributions
Waseem Akhtar has contributed to several significant projects, including 'Redline Pre-Trade Risk', a web application that automates stock trading and performs real-time risk analysis. He has also worked on 'Absolute Insight', a Big Data application that employs machine learning algorithms for data processing and analysis.
Technical Skills and Tools
Waseem Akhtar utilizes various technologies and tools in his work, including Rapid Miner API, Spark ML algorithms, and R programming language for implementing machine learning solutions. He also employs data visualization techniques using High Charts and D3 charting libraries to present analyzed data effectively.