Summary
Rounak Dey is a Staff Data Scientist based in Boston with a Ph.D. in Biostatistics and eight years of experience applying statistical genetics and machine learning to human genetic data for therapeutic target discovery. He has progressed from postdoctoral roles at Harvard T.H. Chan School of Public Health to senior and now staff-level data science positions at insitro, blending rigorous method development with production-minded modeling. His work sits at the interface of biostatistics, statistical genetics, and applied ML, enabling translational insights for drug discovery. Colleagues rely on him for principled statistical solutions that scale from research prototypes to industrial datasets, reflecting both deep academic training and industry impact. An uncommon strength is his ability to translate complex genetic models into actionable hypotheses for therapeutic programs.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Biostatistics, Doctor of Philosophy - PhD, Biostatistics at University of Michigan School of Public Health
Master of Statistics, Statistics and Biostatistics, Master of Statistics, Statistics and Biostatistics at Indian Statistical Institute, Kolkata