Jennifer Thorpe-Moscon, PhD, is a researcher and expert in the leadership behaviors and organizational practices that contribute to or inhibit inclusion. Jennifer plans, manages, and evaluates activities, processes, and operations for the Research Data & Innovation Lab to help drive Catalyst’s thought leadership on gender equity and workplace inclusion. She provides oversight on key research activities and processes, including developing protocols, setting goals, managing team member accountability, ensuring data integrity, and identifying and implementing technologies and tools to improve efficiency and effectiveness. Jennifer plays a vital role in building and maintaining global panels of survey participants to support data collection and analyses across research streams, and offers content and statistical expertise on select research projects, including serving as a part of the Catalyst Inclusion Accelerator core team.
Prior to joining Catalyst, Jennifer worked as a biostatistician at Mount Sinai as well as an instructor of master’s-level statistics at New York University. She has led several research labs of up to 13 researchers in both corporate and academic settings. Additionally, she authored the book How Geek Girls Will Rule the World (2013).
Jennifer received her PhD in social psychology from New York University. She earned a BA in both Psychology, with honors, and Computer Science from Columbia University, where she graduated magna cum laude.
Jennifer's Latest Work
This webinar will discuss the benefits of workplace flexibility, bust myths about flexible work, and arm leaders with the tools they need to establish workplace flexibility.
Learn about the experience of Emotional Tax by women of colour in Canada and the effects of empowering workplaces.
Rapport: Combattre les effets de la charge émotionnelle chez les personnes de couleur au canada grâce à l’autonomisation au sein des milieux de travail
Les femmes de couleur au Canada vivent des impôts émotionnels et ont besoin de lieux de travail plus autonomes.