Ning Leng & Jing Huang

Jing Huang, SVP of Bioinformatics and Data Science at Veracyte

Join us with Ning at Roche-Genentech and Jing at Veracyte to chat about embedding modernized data science solutions in pharma to enable data driven decision making.

portrait of smiling Rachael Dempsey standing in front of off-white wall

Rachael Dempsey - Host

Community Manager at Posit, PBC

I love connecting people across the data science community to share what they're accomplishing with data and help others do the same through community discussions, industry meetups, and more.

Jing Huang

Jing Huang, SVP of Bioinformatics and Data Science at Veracyte

Jing Huang holds a B.A. in Statistics and Probability from Peking University and a Ph.D. in Statistics and M.S. in Epidemiology from Stanford University. With over 20 years in the biomedical field, her research focuses on statistical methodologies in clinical trial design, genomic analysis, and machine learning. As SVP of Bioinformatics & Data Science at Veracyte Inc., she oversees bioinformatics pipelines, algorithm development, and statistical analyses for product development. Jing has co-authored over 30 peer-reviewed articles, with more than ten thousand citations, and is a co-inventor on over 20 patent filings. She actively promotes data science through volunteer work, including as founding president of DahShu, 2024 president of BBSW, and chapter representative of the American Statistical Association San Francisco Bay Area Chapter (SFASA). In 2023, she was elected as a Fellow of the American Statistical Association to recognize her outstanding contributions to the medical research community in the field of statistics; for numerous statistical innovations in genomic tests; and for exemplary leadership and community service to the profession.

Ning Leng

Ad-interim Global Head, Data Sciences Acceleration at Roche-Genentech

Ning Leng is the ad-interim Global Head of the Data Science Acceleration Enabling Platform, under Roche Product Development Data Sciences. Ning joined Roche-Genentech in 2016 as a statistician and worked on both early and late phase oncology development, with a special interest in utilizing diverse data sources and advanced methodologies to generate insights for personalized healthcare. Since then she has been driving a number of internal and cross-industry projects on modernizing Data Science solutions in pharma. Prior to joining Roche-Genentech, Ning obtained her PhD in Statistics from University of Wisconsin-Madison and worked at the Morgridge Institute for Research.