James Paul Astronomo

Data Analyst, Process Manager And Team Master @ Trax Technologies

About James Paul Astronomo

James Paul Astronomo is a data analyst and process manager with a background in accounting. He has over 14 years of experience at Trax Technologies, where he has contributed to logistics data accuracy and predictive analytics solutions.

Work at Trax Technologies

James Paul Astronomo has been employed at Trax Technologies since 2010, serving as a Data Analyst, Process Manager, and Team Master. In this role, he has played a significant part in ensuring the accuracy and reliability of logistics data on the company's cloud platform. He has contributed to the development of predictive analytics solutions, utilizing a vast repository of over 1 billion logistics transactions. His work has focused on optimizing logistics operations across various industries and countries through data-driven insights.

Education and Expertise

James Paul Astronomo earned a Bachelor of Science degree in Accounting from Holy Name University, where he studied from 2003 to 2007. His educational background has provided him with a solid foundation in analytical skills and financial principles, which he applies in his current role as a Data Analyst. His expertise includes data analysis, process management, and team leadership, which he has developed over his career in various positions.

Background

Prior to his current position at Trax Technologies, James Paul Astronomo worked as an Internal Auditor at DU EK SAM, INC. from 2007 to 2008. He then transitioned to a role as a Customer Service Representative at Metropolitan Bank and Trust Company from 2008 to 2009. These early career experiences contributed to his understanding of operational processes and customer service, which he later applied in his data analysis and process management roles.

Achievements

Throughout his career, James Paul Astronomo has been instrumental in optimizing logistics operations for businesses across various industries. His contributions at Trax Technologies have focused on leveraging data to improve operational efficiency and reliability. His role in developing predictive analytics solutions has been crucial in providing businesses with actionable insights derived from extensive logistics data.

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