Shen Gao
About Shen Gao
Shen Gao is a Senior Machine Learning Engineer at Carta, where he has worked since 2022. He has a diverse background in data science and quantitative analysis, with previous roles at various institutions including EY and Morgan Stanley.
Work at Carta
Shen Gao has been employed at Carta since 2022 as a Senior Machine Learning Engineer. In this role, he focuses on developing machine learning solutions, particularly in applications related to large language models (LLMs) and structured document extraction. Prior to his current position, he served as a Lead Data Scientist at Carta from 2020 to 2022, and as a Senior Data Scientist from 2019 to 2020. His tenure at Carta reflects a transition from data science to machine learning engineering, indicating a shift towards more technical responsibilities.
Education and Expertise
Shen Gao holds an Artificial Intelligence Graduate Certificate from Stanford University. He earned a Master’s Degree in Financial Mathematics from New York University and completed a Bachelor's Degree with a double major in Mathematics and Economics at the University of Virginia. His educational background provides a strong foundation for his work in machine learning, where he specializes in entity resolution and event milestone prediction.
Background
Shen Gao has a diverse professional background in quantitative analysis and data science. He began his career as a Quant Analyst at EY from 2012 to 2014, followed by a position as a Quant Associate at AQR Capital Management from 2014 to 2016. He then worked as a Market Risk Manager at Morgan Stanley from 2017 to 2019. His roles have consistently involved data-driven decision-making and analysis, culminating in his focus on machine learning applications.
Previous Experience
Before joining Carta, Shen Gao gained valuable experience as a Graduate Teaching Assistant at New York University from 2017 to 2018. His role involved supporting students in their learning processes, which complements his technical expertise with teaching experience. His progression through various roles in data science and quantitative analysis has equipped him with a comprehensive skill set applicable to his current work.