Ronak Mehta
Quantitative Analyst Intern
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolRonak Mehta is a PhD student in Statistics at the University of Washington with eight years of quantitative and research-focused experience across industry and academia. He blends deep statistical foundations from Johns Hopkins with hands-on machine learning practice at firms including Amazon, Meta, Microsoft, and D. E. Shaw, tackling problems from graph neural networks and time-series forecasting to multimodal inference and large language models. His work spans applied domains—retail forecasting, safety-focused multimodal systems, continual learning, neuroimaging, and financial time series—demonstrating an ability to move methods from research to production. At D. E. Shaw and Amazon he applied state-of-the-art models to business-critical forecasting and LLM problems, while earlier roles emphasized scalable data pipelines and distributed analysis. Colleagues would note his uncommon combination of rigorous statistical thinking with practical engineering for large-scale, real-world datasets.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at University of WashingtonJohns Hopkins University
Github Skills (18)
mutual-information10
sympy9
graph9
wolfram-language9
python8
r-package7
explore7
transfer-learning7
incremental-learning6
machine-learning6
classification6
statistics5
r5
algorithms4
deep-learning4
Programming languages (6)
Github contributions (5)
rmehta004/ta
Oct 2019 - Mar 2020
Teaching Assistant materials, such as section notes, homework solutions, texts, papers, and anything else useful.
Contributions:53 commits in 5 months
notesassistantteachingmachine-learningteaching-assistant
ronakdm/ronakdm.github.io
Dec 2020 - Dec 2025
Contributions:95 pushes, 1 branch in 5 years 1 month
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