Xinxin Xu
About Xinxin Xu
Xinxin Xu is a Demurrage Analyst at ExxonMobil in Budapest, Hungary, specializing in optimizing demurrage processes and strategic negotiations within the oil and gas sector.
Current Role at ExxonMobil
Xinxin Xu currently works as a Demurrage Analyst at ExxonMobil in Budapest, Hungary, starting from 2022. In this role, Xinxin specializes in optimizing demurrage processes to mitigate financial risks within the oil and gas sector. The position involves strategic negotiation, leveraging advanced data analysis to address challenges, and thriving in a collaborative environment under pressure.
Previous Experience at Huawei
Before joining ExxonMobil, Xinxin Xu worked at Huawei as a Logistics Specialist from 2018 to 2020 in Budapest, Hungary. During this period, Xinxin was tasked with managing logistics operations, contributing to the efficiency and effectiveness of the supply chain for the company. The role provided experience in logistical coordination and strategic problem-solving.
Educational Background and Research
Xinxin Xu has a robust academic background, currently a PhD candidate in World Economy at Corvinus University of Budapest, a process ongoing since 2017. Xinxin also holds a Master of Science (MS) degree in International Economy and Business from the same university, completed between 2015 and 2017. Additionally, Xinxin achieved a Bachelor of Arts (BA) degree in English Teaching from Xianyang Normal University, completed between 2011 and 2015. This extensive educational journey has provided a strong foundation in advanced research methodologies and economic dynamics.
Specialization in Demurrage and Negotiation
Xinxin Xu specializes in optimizing demurrage processes, crucial for mitigating financial risks in the oil and gas sector. This specialization is enhanced by strategic negotiation skills, significant for resolving disputes and ensuring favorable outcomes in demurrage cases. The combination of academic rigor and practical experience allows Xinxin to address and manage complex challenges in data analysis effectively.