Summary
Nan Shen is a Senior Machine Learning Engineer based in New York with 13 years of experience and a PhD in Genetics and Data Science, blending deep biomedical expertise with production ML systems. She has led end-to-end projects from novel microbiome time-series algorithms in academic research to deploying glycemic response models and RAG-driven personalized recipe systems at Viome. Currently focused on making American healthcare more acceptable at Sheer Health, she specializes in applying LLM fine-tuning, retrieval-augmented generation, and scalable AWS-based pipelines to clinical and consumer problems. Her work uniquely combines high-impact translational research (faster, more accurate microbiota clustering and discovery of bacterial cliques linked to metabolic outcomes) with demonstrated production metrics (e.g., saliva model AUC 0.99). Known for a curious, product-minded approach—“Stay Hungry, Stay Foolish”—she bridges biology, machine learning, and productization to move models from insight to real-world use.
13 years of coding experience
14 years of employment as a software developer
Bachelor of Science (BS) Biology General, Bachelor of Science (BS) Biology General at Sichuan University
Doctor of Philosophy (PhD) Genetics and Data Science, Doctor of Philosophy (PhD) Genetics and Data Science at Icahn School of Medicine at Mount Sinai
Master's degree Bioengineering and Biomedical Engineering, Master's degree Bioengineering and Biomedical Engineering at Stony Brook University
Japanese, Chinese, English, Spanish