Reema Moussa is an associate in the firm’s Business Law department.
Experience
During her legal studies Reema held positions with a number of different types of stakeholders across the globe, interning at the Federal Trade Commission's Division of Privacy and Identity Protection, VMCA Advogados (São Paulo, Brazil), Goodwin Procter, the Electronic Frontier Foundation, the Future of Privacy Forum, and SentinelOne. She has spoken on her experience and knowledge of interdisciplinary technology law and policy issues at several international conferences, including Women in Cybersecurity (WiCyS), the IAPP Global Privacy Summit, the California Lawyers Association’s annual Privacy Summit, ICANN, and the American Bar Association’s inaugural Consumer Protection and Data Privacy Conference, among others. She previously served as the Vice-President and West Coast Regional Chair of the Internet Law and Policy Foundry, where she was a Senior Fellow and the host/executive producer of the Tech Policy Grind podcast.
Professional Activities
American Bar Association, Antitrust Section, Privacy and Information Security Committee, Young Lawyers Advisory Panel
professional experience
Reema is a Certified Information Privacy Professional (CIPP/US) and a Certified Information Privacy Manager (CIPM).
Credentials
Education
JD2024
University of Southern California, Gould School of Law
Master'sTechnology Management2021
University of California
Santa Barbara
BA2020
University of California
Santa Barbara
(magna cum laude, Phi Beta Kappa)
Admissions
Bars
- New York
Publications
- Co-Author, “Beyond Checkboxes: Privacy Protections That Work for the Future Generation with Lama Mohammed and Meri Baghdasaryan,” Tech Policy Press, October 26, 2023
- Author, “Barnett v. Apple: Privacy by Design as a BIPA Compliance Tool?,” American Bar Association: Antitrust Law Section, Privacy and Information Security (PRIS) Committee, April 6, 2023
- Co-Author, “FinQA: A Dataset of Numerical Reasoning over Financial Data,” Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2021