Poonam Chitale
Business Analyst II at Memorial Sloan Kettering Cancer Center
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolPoonam Chitale is a Business Analyst II based in New York with seven years of interdisciplinary experience bridging life sciences research and data-driven analysis. She holds a PhD in Biology from Rutgers and an MS in Molecular Biology from NYU, and has transitioned from hands-on laboratory roles and academic research to analytics and strategy in healthcare and biotech settings. At Memorial Sloan Kettering and prior firms she applies rigorous experimental thinking to business problems, translating complex technical details into actionable insights. An active contributor to open-source documentation for NVIDIA's NeMo, she enhances accessibility for large-scale generative AI projects—an uncommon nexus of domain science and AI tooling. Colleagues know her for combining meticulous data habits with leadership experience in scientific and startup communities.
7 years of coding experience
4 years of employment as a software developer
Masters, Molecular Biology, Masters, Molecular Biology at New York UniversityBachelor of Science (B.S.), Biology, General, Bachelor of Science (B.S.), Biology, General at The College of New JerseyDoctor of Philosophy - PhD, Biology, Doctor of Philosophy - PhD, Biology at Rutgers University
English, Spanish
Github Skills (7)
documentation10
large-language-models7
generative-ai7
asr7
speech-synthesis7
deep-learning6
machine-translation5
Programming languages (2)
Github contributions (5)
NVIDIA/NeMo
Aug 2019 - Oct 2020
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Role in this project:
Technical Writer
Technical WriterContributions:14 commits, 10 PRs, 4 pushes in 1 year 2 months
Contributions summary:Poonam primarily focused on updating and enhancing the repository's README.rst file. Their contributions involved adding links to documentation, developer blogs, and introductory videos, improving the overall accessibility of the project information. They also updated the content to provide clearer explanations, add installation instructions, and include the latest versions and available resources. These updates indicate a focus on making the project more user-friendly and informative for potential users.
asrspeech-recognitionnatural-language-processingttsspeaker-diarization
gridai/gridai
Apr 2021 - Jul 2021
Placeholder for the opensource Grid AI components
Contributions:7 commits, 2 PRs, 14 pushes in 2 months
gridmachine-learningmlai
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