[Please Note: This session has already occurred. Go to the News Story to read about what happened.]
Interested in a statistics or data science position in the consumer products or pharmaceutical industry? Then this session is for you!
This virtual career fair event is the tenth in a series of Virtual Career Fairs that NISS has been hosting. (Check out earlier virtual career fair sessions!) Some of these session have focused on academic positions, others on positions in government agencies and industry.
This session features opportunities for statisticians/data scientists from three companies. Senior statisticians from Procter & Gamble Company, Merck & Co. and Eli Lilly and Company will be on hand to provide attendees with an inside look at the research that statisticians in these companies get involved in and career opportunities for you to consider!
Each presenter will have 15 minutes to address the following general topics:
- What are the job opportunities for statisticians/data scientists/analysts in your company?
- Describe the range of skills statisticians/data scientists/analysts need to succeed in your company?
- What is the career path for statisticians/data scientists/analysts in your company?
- Is your firm currently hiring statisticians/data scientists/analysts?
- What advice would you give to students based on your experience?
Registration Process
Please use your .edu, .gov or .com email address when registering. The Career Fair will be conducted using Zoom.
REGISTER FOR THIS EVENT HERE!
Agenda
The program for this virtual career fair will be organized as follows:
12:00-12:05 Opening remarks: Moderator: Ying Ding (U Pitt, Biostatistics)
12:05-12:20 William Brenneman (Procter & Gamble) "Practicing Statistics and Data Science at P&G"
12:20-12:35 Junshui Ma (Merck) "Statisticians’ Jobs in Merck"
12:35-12:50 Wei Shen (Eli Lilly) "Life of a Statistician at Lilly"
12:50-1:30 Q&A
About the Presenters:
William Brenneman is a Research Fellow and Global Statistics Discipline Leader at Procter & Gamble in the Data and Modeling Sciences Department and an Adjunct Professor of Practice at Georgia Tech in the Stewart School of Industrial and Systems Engineering. Since joining P&G in 2000, he has worked on a wide range of projects that deal with statistics applications. He was also instrumental in the development of an in-house statistics curriculum. He received a Ph.D. degree in Statistics from the University of Michigan, an MS in Mathematics from the University of Iowa and a BA in Mathematics and Secondary Education from Tabor College. William is a Fellow of the American Statistical Association (ASA), a Fellow of the American Society for Quality (ASQ), and a member of the Institute of Mathematical Statistics and the Institute for Operations Research and Management Sciences. He has served as ASQ Statistics Division Chair, ASA Quality and Productivity Section Chair and is currently serving as an Associate Editor for Technometrics. William also has seven years of experience as an educator at the high school and college level.
Junshui Ma is currently a Senior Director at Merck and leads the Translational Oncology Statistics group. He obtained his Ph.D. from Ohio State University in 2001. He worked in Los Alamos National Lab, Aureon Bioscience and Ohio Supercomputer Center, before he joined Merck in January 2005. In the past 16 years of working at Merck, he engaged in all phases of drug Research & Development (R&D), including preclinical discovery, clinical development, regulatory filing, and translational medicine. His research interests include machine learning in pharmaceutical R&D, stratified medicine, and survival analysis. He coauthored 30 peer-reviewed journal papers, along with many conference abstracts and posters.
Wei Shen is Senior Director, Statistics, Data and Analytics at Eli Lilly and Company. He received his Ph.D. in Biostatistics from University of Minnesota in 1996. During his 25-year career at Lilly, he made substantial contributions to drug development in osteoporosis, men’s health, autoimmune disorders, and COVID. He is a Fellow of the American Statistical Association. From 2017-2018, he was a member and chair of the ASA committee of nominations. He has been a long-time contributor to the International Chinese Statistical Association (ICSA), serving as President of the ICSA in 2015. From 2013 to 2017, he was an Associate Editor for Journal of Biopharmaceutical Statistics. He has contributed to 50+ publications on statistical methodology and medical research.
Ying Ding is an Associate Professor at the Department of Biostatistics, University of Pittsburgh. She received her Ph.D. in Biostatistics from University of Michigan in 2010. Before joining University of Pittsburgh, Dr. Ding worked as a Senior Research Scientist at Eli Lilly and Company, and her responsibility at Lilly focused on Type II Diabetes trials. Currently, Dr. Ding’s research interests include survival analysis, large-scale multi-omics data analysis, multiple comparisons, and precision medicine. Her collaborative research includes cancer clinical trials, disease progression modeling and prediction for aging-related disorders. Currently, she is the NISS liaison for her department. She also serves as ASA Pittsburgh Chapter 2021 President, ASA Lifetime Data Science (LiDS) Section 2022 Program Chair-Elect, and ASA Statistical Partnership Across Academe, Industry & Government (SPAIG) Committee Vice Chair.
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- NISS Hosted
- NISS Sponsored
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