Zahra Navidi, PhD
About Zahra Navidi, PhD
Zahra Navidi, PhD, is a Manager of Modelling and Data Science Projects at KPMG Australia, where she has worked since 2021. She has a diverse background in transport modelling, data science, and engineering, with experience at various institutions including AECOM and the University of Melbourne.
Work at KPMG Australia
Zahra Navidi has been employed at KPMG Australia as a Manager in Modelling and Data Science Projects since 2021. In this role, she oversees various projects in Melbourne, Victoria, focusing on the application of data science techniques to solve complex problems. Her responsibilities include managing digital transformation efforts, transitioning on-premises infrastructure to cloud-based solutions, and conducting client training sessions. She also communicates complex model features and project outcomes to clients with varying technical backgrounds.
Education and Expertise
Zahra Navidi holds a Doctor of Philosophy (Ph.D.) in Engineering from the University of Melbourne, where she studied from 2014 to 2019. She also earned a Master's Degree in Transportation Systems from the Technical University of Munich between 2011 and 2014. Additionally, she completed her Bachelor's degree in Civil Engineering at K. N. Toosi University of Technology from 2006 to 2010. Her academic background equips her with a strong foundation in engineering principles and data analysis.
Background
Zahra Navidi began her professional career as an intern at AUDI AG in Germany in 2013. She later worked as a Researcher at the same company for five months. After returning to Australia, she served as a Tutor at the University of Melbourne in 2015 and then as a Ph.D. candidate from 2014 to 2019. Following her doctoral studies, she gained experience as a Senior Consultant in Management Consulting at KPMG Australia from 2019 to 2020, and then worked at Veitch Lister Consulting as a Senior Consultant in Modelling until 2021.
Achievements
Zahra Navidi has contributed to various projects throughout her career. She developed Python-based analytical tools aimed at supporting policy development for reducing uptake costs and maximizing benefits of Distributed Energy Resources (DERs). Additionally, she led a team of five modellers and consultants to deliver an agent-based model that projects future changes in transport and travel patterns, utilizing Java. Her ability to communicate complex model features effectively is a key aspect of her work.