Sepide Zakeri, Ph.D.
About Sepide Zakeri, Ph.D.
Sepide Zakeri, Ph.D., is a Senior Applied ML Scientist at Seeq Corporation, where she has worked since 2022. She holds a Ph.D. in Petroleum Engineering from The University of Tulsa and has experience in analytics and petroleum engineering.
Work at Seeq Corporation
Sepide Zakeri, Ph.D., has been employed at Seeq Corporation since 2022 as a Senior Applied ML Scientist (Applications). In this role, she focuses on applying machine learning techniques to enhance the company's analytics capabilities. Prior to her current position, she served as a Senior Analytics Engineer at Seeq from 2021 to 2022, and as an Analytics Engineer from 2018 to 2021. Her tenure at Seeq has contributed to the development of innovative solutions in the field of data analytics.
Education and Expertise
Sepide Zakeri holds a Doctor of Philosophy (Ph.D.) in Petroleum Engineering from The University of Tulsa, where she studied from 2016 to 2019. She also earned a Master of Science (M.S.) in Petroleum Engineering from the same institution, completing her studies from 2013 to 2015. Additionally, she obtained a Master's degree in Instrumentation and Automation Engineering from the Petroleum University of Technology. Her educational background is complemented by a Bachelor's degree in Electrical and Electronics Engineering from Ferdowsi University of Mashhad.
Previous Experience in Petroleum Engineering
Before her roles at Seeq Corporation, Sepide Zakeri gained experience as an Artificial Lift Services–Petroleum Engineering Intern at Schlumberger in 2014. This internship lasted for three months and took place in the Houston, Texas area. Her early career experiences laid the groundwork for her expertise in petroleum engineering and analytics.
Career Progression
Sepide Zakeri's career at Seeq Corporation reflects a steady progression in her field. She began as an Analytics Engineer in 2018, transitioned to a Senior Analytics Engineer in 2021, and then advanced to her current role as Senior Applied ML Scientist (Applications) in 2022. This trajectory demonstrates her growing expertise and contributions to the field of machine learning and data analytics.