Can you do research while being in a industry setting? How do people do science in real world ? What are some technical and cultural difference between statistics and machine learning? Jonathan O'Brien will answer all these questions for you! Jonathan obtained his PhD degree in biostatistics from University of North Carolina and currently works as a principle data scientist in Calico life science which is a health care biotech company that focuses on combating aging and aging related diseases. His main research interest has been focused on improving the mathematical modeling and downstream analysis of mass spectrometry proteomics experiments which involves missing data techniques, Bayesian hierarchical modeling, clustering and compositional data analysis. It was great talking to Jonathan since he gave me a lot of new perspectives, and I learned a lot more about proteomics studies and what he is working on. Let's dive into this episode to see what Jonathan shared with us! The paper mentioned in this episode can be found here: The effects of nonignorable missing data on label-free mass spectrometry proteomics experiments. Please visit our website https://biostatisticspodcast.github.io/ for the latest updates and transcripts of the published episodes. If you have any comments, feedback or suggestions, feel free to email us via [email protected] or DM us on Twitter @BiostatsPodcast Powered by Firstory Hosting