Summary
Noah Kasmanoff is a Senior Data Scientist in New York with nine years of experience applying machine learning and signal-processing techniques across space science, healthcare, finance, and product analytics. Trained in physics and astronomy and holding an MS in Data Science from NYU, he has built simulation-driven detector models for NASA missions, led an FDL team that created LLM-based disaster reporting tools, and produced deep-learning pipelines for medical imaging with published results. He combines strong Python engineering, data wrangling, and visualization skills with hands-on experience shipping ML-backed web portals and automations that saved operational time at nonprofits and startups. Noah’s work bridges research and production—translating NeurIPS-accepted research and NASA prototypes into practical tools—and he enjoys tackling problems where noisy real-world data meet domain knowledge. Colleagues describe him as a creative thinker who moves quickly from prototypes to deployable systems while keeping model trust and efficiency front of mind.
9 years of coding experience
7 years of employment as a software developer
Master's degree, Data Science, Master's degree, Data Science at New York University
Physics and Astronomy, Physics and Astronomy at University of Maryland
English