Michal Nitzani
About Michal Nitzani
Michal Nitzani is a Data Engineer at Trax Retail since 2021, with previous experience as a Solution Architect Team Lead at Optibus. Nitzani holds a PhD in Industrial Engineering and has a strong interest in optimization and transportation planning.
Work at Trax
Michal Nitzani has been employed as a Data Engineer at Trax Retail since 2021. In this role, Nitzani applies expertise in data engineering to support the company's operations. The position involves working with data systems and contributing to projects that enhance data-driven decision-making within the retail sector.
Previous Experience at Optibus
Before joining Trax, Nitzani held multiple roles at Optibus, including Solution Architect Team Lead from 2018 to 2020 and Solution Engineer from 2017 to 2018. Nitzani also briefly served as the Director of Innovation in 2017. These positions involved leading teams and developing solutions in the transportation planning sector, leveraging data to optimize operations.
Education and Expertise
Nitzani has a strong educational background, having earned a Doctor of Philosophy (PhD) in Industrial Engineering with a focus on Transportation Research from Ben-Gurion University of the Negev from 2008 to 2015. Additionally, Nitzani holds a Master of Science (MSc) in Industrial Engineering and a Bachelor of Science (BSc) in Information Systems Engineering, both from the same institution. This comprehensive education supports Nitzani's expertise in data engineering and transportation planning.
Academic Background
Nitzani worked as a lecturer at Ruppin Academic Center from 2012 to 2017, teaching courses related to engineering and data science. This experience in academia highlights Nitzani's commitment to education and knowledge sharing in the field of industrial engineering and transportation.
Interest in Optimization
Nitzani has a strong interest in optimization, which is a crucial aspect of data science and transportation planning. This interest informs Nitzani's work as a data engineer, where optimizing data processes and systems is essential for improving efficiency and effectiveness in projects.