Sheng Wang
About Sheng Wang
Sheng Wang is a Principal Data Scientist at Mathematica, where he has worked since 2022. He specializes in developing statistical models and data visualization tools to support policy-making and enhance decision-making processes for clients.
Work at Mathematica
Sheng Wang currently serves as Principal Data Scientist at Mathematica, a position he has held since 2022 in New Jersey, United States. Prior to this role, he worked as a Lead Data Scientist from 2020 to 2022, also in New Jersey. His career at Mathematica began as a Senior Statistician, where he contributed from 2017 to 2020 in Princeton. Throughout his tenure, he has focused on supporting policy-making through data-driven evidence and the development of statistical models.
Education and Expertise
Sheng Wang holds a Doctor of Philosophy (Ph.D.) in Statistics from the University of Wisconsin-Madison, where he studied from 2006 to 2011. He also earned a Bachelor of Science (BS) in Mathematics from Tsinghua University, completing his studies from 2002 to 2006. His educational background provides a strong foundation for his expertise in statistical modeling, machine learning, and data mining.
Background
Sheng Wang's professional background includes extensive experience in data science and statistics. He has developed a range of data visualization, matching, and measurement products aimed at enhancing model usability. His work is geared towards supporting real-time decision-making for clients, showcasing his commitment to applying statistical methods in practical settings.
Achievements
In his role at Mathematica, Sheng Wang has made significant contributions to the field of data science. He supports policy-making by providing robust statistical models for statistical and causal inference. His application of machine learning and data mining tools has facilitated the creation of useful tools that streamline decision-making processes for clients.