Jeffrey Javed
About Jeffrey Javed
Jeffrey Javed is a Staff Growth Researcher at Apollo.io, specializing in integrating machine learning with various research methodologies. He has a strong academic background, including a PhD from Harvard University, and has held research positions at notable institutions such as Meta and the University of Michigan.
Current Role at Apollo.io
Jeffrey Javed serves as a Staff Growth Researcher at Apollo.io, a position he has held since 2024. His role focuses on enhancing growth strategies through research methodologies. He is based in San Francisco, California, where he contributes to the development of data-driven insights that support the company's objectives.
Previous Experience at Shopify
In 2022, Jeffrey Javed worked at Shopify as a Senior Staff Product Researcher for a brief period of two months. His responsibilities included conducting product research to inform decision-making processes within the organization. This role was located in the United States.
Academic Background at Harvard University
Jeffrey Javed has an extensive academic background at Harvard University. He was a PhD Candidate from 2012 to 2017, specializing in Government. During this time, he also served as a Teaching Fellow and later as Head Teaching Fellow in 2016. His teaching roles spanned several months, contributing to the academic development of students.
Research Experience at Meta
Jeffrey Javed worked at Meta from 2019 to 2023, where he held various positions including Mixed Methods Researcher in Core Ads and Staff Mixed Methods Researcher in Monetization. His work involved applying mixed methods research to enhance advertising strategies and product development.
Publications and Research Focus
Jeffrey Javed authored the book 'Righteous Revolutionaries,' published by the University of Michigan Press in 2022. The book examines state-mobilized violence in Maoist China. His research interests include Chinese politics, political mobilization, and collective memory, utilizing diverse methodologies such as machine learning and semi-structured interviews.