Cynthia (Jeruto) Bundi
About Cynthia (Jeruto) Bundi
Cynthia (Jeruto) Bundi is a Quantitative Research Associate at Harvard Business School, specializing in peer influence dynamics and causal inference techniques in social networks. She holds a degree in Quantitative Social Science from Dartmouth College and has experience in various research and analytical roles.
Current Position at Harvard Business School
Cynthia Bundi serves as a Quantitative Research Associate at Harvard Business School, a role she has held since 2021. In this position, she applies her expertise in quantitative analysis to support research initiatives. Her focus includes utilizing machine learning and causal inference techniques to address social impact challenges. Bundi's work contributes to the understanding of complex social network structures through the application of graph theory principles.
Educational Background
Cynthia Bundi studied at Dartmouth College from 2017 to 2021, where she earned a degree in Quantitative Social Science. During her time at Dartmouth, she also participated in the Tuck Liberal Arts and Business Program at The Tuck School of Business in 2019. Prior to her college education, she completed her high school studies at Alliance Girls High School from 2012 to 2015.
Professional Experience
Before her current role, Bundi gained diverse experience through various internships and positions. She worked as a Data Research Associate at Inclusive America for one month in 2021 and as a Strategic Planning Intern at DOWA - Doing Good Work in Africa for two months in the same year. Additionally, she volunteered with Statistics Without Borders for two months in 2021. Her earlier roles at Dartmouth College included serving as a Quantitative Analysis Tutor and a Student Assistant, where she contributed to academic support from 2018 to 2021.
Research Focus and Expertise
Cynthia Bundi specializes in peer influence dynamics and their implications in social media environments. Her research incorporates causal inference techniques and anomalous subset scanning, a method for detecting unusual patterns in data. Bundi's application of machine learning in her research aims to develop innovative solutions for social impact challenges, enhancing the understanding of social networks.
Internship Experience
Cynthia Bundi has completed several internships that have shaped her professional development. In 2016, she interned at Equity Bank Limited in Nairobi, Kenya, for three months. Her subsequent internships in 2021 included roles at Inclusive America and DOWA - Doing Good Work in Africa, where she gained valuable insights into data research and strategic planning.