Wei Song

Wei Song

Principal Software Engineer @ Thomson Reuters

About Wei Song

Wei Song is a Principal Software Engineer at Thomson Reuters in Beijing, China, specializing in data mining for fixed income. He holds a Bachelor's degree in Information Engineering and a Master's degree in Communication & Electronic System from Xidian University.

Work at Thomson Reuters

Wei Song has been employed at Thomson Reuters as a Principal Software Engineer since 2008. Over the course of 16 years, he has contributed to various projects and initiatives within the organization. His role involves utilizing advanced technologies and methodologies to enhance data processing capabilities, particularly in the area of fixed income data.

Education and Expertise

Wei Song holds a Bachelor's degree in Information Engineering from Xidian University, where he studied from 1989 to 1993. He furthered his education at the same institution, earning a Master's degree in Communication & Electronic System from 1995 to 1998. His academic background supports his specialization in data mining for fixed income, encompassing data capture, parsing, loading, normalization, and transformation.

Technical Skills and Technologies

In his current role, Wei Song employs a variety of programming languages and technologies, including Perl, C/C++, SQL, Java, and shell scripting. His technical skills enable him to effectively manage and process large datasets, ensuring data integrity and accuracy within fixed income markets.

Data Processing Projects

Wei Song developed a significant data process performance promotion project that optimizes the processing of 500,000 data records during specific payment days each month. This project highlights his capability in managing large-scale data operations and improving processing efficiency.

Experience in Fixed Income Data

Wei Song has extensive experience in verifying the integrity and accuracy of fixed income data. He supports the maintenance of timely data, ensuring that critical information is available when needed. Additionally, he is experienced in computing prepayments data on summarized pools, specifically collateral and bonds.

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