Marina Shah
About Marina Shah
Marina Shah is a Staff Data Scientist currently employed at Lexion in Seattle, Washington. With a background in machine learning and natural language processing, she has held various roles in the tech industry since completing her studies in Computational Linguistics and Mathematics.
Work at Lexion
Marina Shah currently holds the position of Staff Data Scientist at Lexion, having transitioned into this role in 2023. Prior to this, she served as a Senior Data Scientist at the same company since 2021, contributing to various data-driven projects. Her journey at Lexion began in 2019 when she joined as a Machine Learning Engineer, a position she held until 2021. Throughout her time at Lexion, Marina has focused on applying her expertise in data science and machine learning to enhance the company's offerings.
Previous Experience in Data Science
Before her tenure at Lexion, Marina worked as an NLP Data Scientist at LivePerson from 2018 to 2019. In this role, she specialized in natural language processing, contributing to the development of AI-driven solutions. Additionally, she gained experience as a Machine Learning Engineer at Bose from 2017 to 2018, where she worked on machine learning applications in the audio technology sector. These positions helped her build a strong foundation in data science and machine learning.
Education and Expertise
Marina Shah earned her Master’s degree in Computational Linguistics from the University of Washington, where she studied from 2016 to 2017. Her academic background also includes a Bachelor’s degree from the University of Illinois Urbana-Champaign, where she studied Mathematics and German. This educational foundation has equipped her with the analytical skills and technical knowledge necessary for her roles in data science and machine learning.
Background
Marina Shah has a diverse professional background in data science and machine learning, with significant experience in both academic and industry settings. She began her career as a Master Student at the University of Washington, where she focused on computational linguistics. Following her studies, she entered the workforce, taking on various roles that allowed her to apply her skills in real-world applications, particularly in natural language processing and machine learning.