Vahab Najari
About Vahab Najari
Vahab Najari is a Senior Data Scientist at ProcessMiner Inc. in the Atlanta Metropolitan Area, specializing in machine learning pipelines for predictive analysis in manufacturing processes.
Work at ProcessMiner
Vahab Najari has been employed at ProcessMiner Inc. since 2021, currently holding the position of Senior Data Scientist. His role involves designing and implementing machine learning pipelines aimed at predictive analysis within complex manufacturing processes. Prior to his current position, he worked as a Data Scientist at ProcessMiner from 2019 to 2021, where he contributed to the development of an autonomous optimization engine as part of the Industry 4.0 implementation. He also served as a Data Science Intern at the company in 2018 for seven months.
Education and Expertise
Vahab Najari earned a Master of Business Administration (MBA) from the University of Tehran, where he studied Business Administration and Management from 2013 to 2016. He furthered his education at Georgia State University - J. Mack Robinson College of Business, obtaining a Master of Science (MS) in Analytics (Data Science) from 2017 to 2018. His undergraduate studies were completed at K. N. Toosi University of Technology, where he received a Bachelor of Engineering (BEng) in Electrical and Electronics Engineering from 2008 to 2013.
Background
Before joining ProcessMiner, Vahab Najari worked at Georgia State University - J. Mack Robinson College of Business. He held the position of Graduate Research Assistant (Data Analyst) for four months in 2017 and subsequently served as a Legal Analytics Lab Data Analyst - GRA for four months from 2017 to 2018. His experience in academia provided him with a solid foundation in data analysis and research methodologies.
Achievements
During his tenure at ProcessMiner, Vahab Najari developed an autonomous optimization engine, which played a significant role in the company's Industry 4.0 initiatives. His expertise in machine learning and predictive analytics has contributed to advancements in manufacturing processes, showcasing his ability to apply theoretical knowledge to practical applications.