Hanzhi (Ella) Zhou
About Hanzhi (Ella) Zhou
Hanzhi (Ella) Zhou is a Senior Data Scientist at Mathematica, where she has worked since 2014. She holds a PhD in Statistics/Survey Methodology from the University of Michigan, where she also served as a Research and Teaching Assistant from 2009 to 2014.
Work at Mathematica
Hanzhi (Ella) Zhou has been employed at Mathematica as a Senior Data Scientist since 2014. In this role, she applies her expertise in data analysis and statistical methodologies to support various projects. Her work contributes to Mathematica's mission of improving public policy and social programs through data-driven insights. Zhou's tenure at the organization spans over ten years, during which she has engaged in numerous initiatives aimed at enhancing research outcomes.
Previous Experience at University of Michigan
Prior to her current position, Hanzhi (Ella) Zhou worked at the University of Michigan from 2009 to 2014. During her five years there, she served as both a Research and Teaching Assistant. This role involved supporting faculty in research projects and assisting in the instruction of undergraduate courses. Her experience at the university provided her with a solid foundation in statistical analysis and research methodologies.
Education and Expertise
Hanzhi (Ella) Zhou earned her Doctor of Philosophy (PhD) in Statistics/Survey Methodology from the University of Michigan. Her academic journey spanned from 2009 to 2014, during which she developed a strong proficiency in statistical techniques and survey research. This educational background underpins her current work as a Senior Data Scientist, where she utilizes her knowledge to analyze complex data sets and inform decision-making processes.
Background
Hanzhi (Ella) Zhou has a background in statistics and survey methodology, having focused her studies on these areas during her time at the University of Michigan. Her experience as a Research and Teaching Assistant provided her with practical skills in data analysis and research design. This foundational knowledge has been instrumental in her career as a data scientist, where she continues to apply her expertise in various research contexts.