Ronak Mehta
Quantitative Analyst Intern
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 (27)
mutual-information10
correlation10
arxiv10
sympy9
probability9
climate-science9
quantile9
statsmodels9
entropy9
wolfram-language9
uncertainty9
python8
ensembles8
graph8
r-package7
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/ml-interviews
Apr 2022 - Dec 2022
Contributions:11 commits, 9 pushes, 1 branch in 8 months
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