Marcia Levenstein is a biostatistician and bioethicist with expertise in clinical research, real-world evidence, and the ethical application of artificial intelligence and machine learning in health data analysis. A former vice president of statistics at Pfizer, she led global biometrics strategies across therapeutic areas and played a key role in clinical trial policy, bioethics, and data transparency.
Levenstein provides advisory leadership on the use of statistics and AI/ML for secondary data analysis at Vivli and has served on academic, AI/ML start-up, and professional ethics boards. She holds undergraduate degrees in mathematics and life sciences from MIT and advanced degrees in biostatistics from Harvard and The University of North Carolina and bioethics from the University of Pennsylvania.
The following interview was performed by the New York City Chapter’s executive committee members.
Looking back at the New York City Chapter’s 90-year journey, what was your role and what were some significant contributions to the statistical community locally and nationally?
I have been a member of the NYC Chapter of the ASA since I returned to New York City and started working. After reconnecting with statisticians I knew from college, I joined the executive committee and chaired the membership committee. For several years, I led this committee and eventually moved to the role of treasurer for the chapter. I continued in that role for most of the years until the present time.
Over these years, I have been involved with planning and organizing many of the chapter’s activities, including symposia, short talks, focused full-day workshops on newly emerging topics, career workshops at local schools, speaker engagements with students about a career in statistics, and poster competitions. The chapter has hosted traveling courses from the ASA. Recently, these were remote courses, but they were in person earlier and provided local members with the opportunity to hear from leading national statistical speakers.
These activities were tailored to meet the varying needs and interests of chapter members and to promote statistics among students to help the profession continue to grow.
How has your involvement with the NYC Chapter shaped your own professional path?
I have fond memories of coordinating and judging poster competitions for NYC students ranging from elementary to high school. Workshops in focused areas such as forecasting, meta-analysis, large language models, machine learning, and ethical issues in analytics were highlights over the past years. We have held refresher courses many times to benefit members who wanted to keep their skills up to date. The topics covered in the course have been updated as methodologies advance to reflect the current state of the art. Recently, we partnered with Regeneron to cosponsor a workshop on innovative statistical methods and with a local nonprofit, AI4Purpose, to cosponsor a workshop on AI.
My involvement with the chapter has led to connections with other statisticians I would have not otherwise met and broadened my perspective on the profession. I had many chances to network with statisticians from different industries. We have partnered with other chapters, local universities, and technical companies to provide forums for our members to learn. The chapter has continued to provide symposia, either in person or remotely, which have been extremely popular with chapter members. The benefit of offering short talks is that it enables us to cover many topics for our membership, which has diverse needs. We have been able to leverage local talent in a variety of venues.
In addition to my role in the NYC Chapter, I was a member of the Committee on Professional Ethics, which updated the ASA Ethical Guidelines for Statistical Practice. In this work and our recent outreach, we are ensuring that we collaborate with professionals who might not think of themselves as statisticians. We are focused on bringing together statisticians, data scientists, and AI practitioners, rather than creating barriers.
As the chapter moves beyond its 90th year, what short- and long-term opportunities or challenges do you anticipate for statisticians, and how should the chapter evolve to meet them?
As we look at the next 10 years, it will be critical for us to continue to promote statistical principles and best practices as we collaborate across the entire spectrum of professions that utilize data. The need for technical excellence and capabilities will continue to be essential, but we need to recognize that effective communication is key for our success. While we may depend on quantitative methods and numbers to understand the world, we need to communicate through stories so that others understand us to be influential.
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