Laz Bello
About Laz Bello
Laz Bello is the Scientific Computing Supervisor at ExxonMobil, overseeing a team that provides custom solutions in various scientific and technical areas.
Professional Role at ExxonMobil
Laz Bello currently serves as the Scientific Computing Supervisor at ExxonMobil. He has held this position since 2020 in Clinton, New Jersey. In this role, he supervises a large group of highly technical direct reports, including PhDs, matching their skills to the highest priority research needs. His responsibilities include performing quarterly portfolio reviews with senior management to collaborate on continued funding and prioritization of projects.
Previous Roles at ExxonMobil
Before his current role, Laz Bello held various positions at ExxonMobil. From 2016 to 2020, he worked as an IT Advisor/Business Solution Advisor for ExxonMobil R&D in Clinton, New Jersey. He was a Change Management Integrator for Skype for Business from 2014 to 2016 in Spring, Texas, and a SharePoint Technical Support Analyst from 2012 to 2014 in Houston, Texas. He also served as a SharePoint Operations Analyst from 2011 to 2012, reflecting a strong progression through multiple technical roles within the company.
Educational Background
Laz Bello has an extensive educational background. He earned a Master's degree in Information Systems and Operations Management (ISOM) from the University of Florida in 2011. Prior to that, he completed a Bachelor of Science in Finance from the same institution, studying from 2002 to 2006. His academic credentials have provided a solid foundation for his various roles in the field of information systems and finance.
Project Management and Team Leadership
Laz Bello has demonstrated strong project management and team leadership skills. He successfully guided a team through logistical challenges during the COVID-19 pandemic to complete the installation of a new high-performance computing cluster involving multiple vendors. Additionally, he collaborates with the law department to navigate US export control laws, enabling an international staffing model with significant projected cost savings.
Collaborative Research and Development
In his role, Laz Bello partners in research across various scientific areas. These include mathematical optimization, modeling, machine learning, deep learning, data analytics, bioinformatics, and manufacturing and industrial processes. He manages a team that provides custom solutions in areas such as algorithms implementation, architecture design, benchmarking, parallelism, data processing, optimization, visualization, and workflow automation.