About

Amir Meimand is an accomplished data scientist and machine learning expert with almost a decade of experience in the field. Currently, he is working as a Principal Solution Engineer for Data Science and Machine Learning at Salesforce, where he is responsible for developing and executing adoption and sales plans, as well as driving Proof of Concepts and Guided Evaluations for businesses. Amir's expertise lies in the areas of machine learning, predictive analytics, optimization, and prescriptive analytics. He has a strong educational background, having earned a Doctor of Philosophy (PhD) in Industrial Engineering and Operations Research from Penn State University and a Master's degree in the same field from Amirkabir University of Technology - Tehran Polytechnic. Throughout his career, Amir has held a variety of roles in different organizations, including Strategic Sales Consultant at Salesforce and Director of Data Science at Zilliant. In his previous role at Zilliant, he oversaw the design, development, and execution of machine learning-based price and sales optimization models in North America. Amir's technical skills include expertise in machine learning, data science, and Salesforce. He is a highly motivated and results-driven individual who is passionate about using data and analytics to drive business growth and success. With his strong analytical and problem-solving skills, he is able to identify and implement the most effective solutions to complex business challenges. Overall, Amir Meimand is a highly experienced and skilled data scientist and machine learning expert who has a proven track record of success in the field. He is a valuable asset to any organization that is looking to leverage data and analytics to drive growth and success.