NISS Virtual Government Career Fair

Wednesday, October 11, 2023 - 12 pm - 1:30 pm ET


Government institutions have a unique mission when it comes to the data they collect as well as the importance of the research they engage in. This research becomes the principle foundation for informing policy issues that impact all aspects of society. So what kinds of opportunities are there for data scientists in the federal government? More importantly, how do you prepare yourself for obtaining a position?

Once again, NISS has gathered an incredible lineup of speakers.  Not only do they bring extensive experience working in the federal government, but these individuals have as their priority a willingness to share their experiences so that others may better understand and be better prepared for working for a federal agency. After each speakers' presentations, we will have an interactive Q&A session with the participants.

Each presenter will have 15-20 minutes to address the following general topics:

  1. What are the job opportunities for statisticians/data scientists/analysts in your agency?
  2. Describe the range of skills statisticians/data scientists/analysts need to succeed in your agency?
  3. What is the career path for statisticians/data scientists/analysts in your agency?
  4. Is your agency currently hiring statisticians/data scientists/analysts?
  5. What advice would you give to students based on your experience?

This is not a session to be missed!


Cha-Chi Fan, Director, Office of Data Development and Standards at Bureau of Transportation Statistics, U.S. Department of Transportation

Shanti V. Gomatam, Mathematical Statistician, Food & Drug Administration

Jonah L. Wong, Mathematical Statistician, U.S. Census Bureau


Lu Chen, NISS & NASS

About the NISS Virtual Career Fair Series

This event is part of the NISS Virtual Career Fair Series: webinars where experienced statisticians from industry, government and academia talk about and provide advice for individuals interested in pursuing a career as a statistician. For more information about these events, please visit:

About the Speakers

Cha-Chi Fan is the Director of the Office of Data Development and Standards in the Bureau of Transportation Statistics (BTS). She leads BTS data development programs, including data collections from surveys and alternative data sources, to support transportation decision making. She also guides BTS’ efforts in statistical standards, data quality, and confidentiality protection. Prior to joining BTS in 2019, she has had professional experience with multiple federal and private organizations, including Federal Communications Commission, U.S. Census Bureau, Energy Information Administration, and RAND Corporation. Dr. Fan has a Ph.D. in natural resources and environmental sciences and a M.S. in statistics from University of Illinois at Urbana-Champaign.

Shanti Gomatam has worked for the Center for Drug Evaluation and Research (CDER) and the Center for Devices and Radiological Health (CDRH) of the US Food and Drug Administration collectively for over 20 years. She is currently with the division that deals with quantitative safety in CDER’s Office of Biostatistics. She has wide-ranging statistical interests; including methodology associated with randomized clinical trials and observational studies, with a recent focus on causal inference. Prior to joining the FDA she held positions at the University of Florida, the University of South Florida and the National Institute of Statistical Sciences.

Jonah L. Wong is a Mathematical Statistician at the U.S. Census Bureau and has coordinated the recruitment and retention programs for methodology staff for the past 12 years and managed a study on Decennial operations for the previous 3 years. Before the Census Bureau, Jonah was an educational researcher at a community college in California for over 17 years. Jonah has a Master's in statistics from California State University, East Bay and earned his undergraduate degree in statistics from the University of California, Berkeley.

Event Type


National Institute of Statistical Sciences


Online Webinar
United States