Nick Eriksson

Nick Eriksson is an accomplished data scientist and statistician with extensive experience in machine learning and statistical genetics. Nick served as Principal Data Scientist at CalicoLabs, where innovative machine learning models for biological age were developed. Prior experience includes roles as NSF Postdoctoral Fellow at Stanford University focusing on Bayesian networks for HIV drug resistance, Visiting Assistant Professor at the University of Chicago with contributions to high-throughput sequencing analysis, and Data Scientist at Coursera, where significant projects included personalized course recommendations and retention prediction models. Nick also held multiple positions at 23andMe, including Statistical Geneticist and Principal Scientist, where foundational research in human genetics and the analysis of complex traits was conducted. Educational qualifications include a PhD in Mathematics from the University of California, Berkeley, and a Bachelor's Degree in Mathematics from the Massachusetts Institute of Technology.