Summary
Anna Shors is a Deep Learning Algorithm Engineer at NVIDIA with five years of experience bridging pure mathematics and applied machine learning. With dual training in mathematics (University of Rochester) and data science (Stanford), she has contributed to research on variational EM for social networks, L2 regularization variants for NLP, and sum-product estimates in finite fields. Proficient in Python, R, and Java, she has taught data analysis in R and translated theoretical insights into practical deep learning solutions, particularly in named entity recognition. Based in San Francisco, she enjoys tackling combinatorics-flavored ML problems and brings a problem-solver's curiosity—honed by math competitions and Rubik’s cubes—to engineering research and production-grade algorithm development.
5 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Mathematics, Bachelor's degree, Mathematics at University of Rochester
Master's degree, Data Science, Master's degree, Data Science at Stanford University