Rushabh Vasani
Senior Data Scientist
Bengaluru, Karnataka, India
Summary
👤
Senior🎓
Top SchoolRushabh Vasani is a Senior Data Scientist based in Bengaluru with 7 years of experience building production-grade AI systems, currently focusing on scalable medical-document-understanding and ML pipelines at eka.care. He has progressed internally from intern to senior role, shipping systems that extract actionable insights from health records and powering a smart health locker product. An active open-source contributor, Rushabh has improved core ML and scientific Python libraries—contributing bug fixes and modernizations to scikit-learn, pandas, IPython, CuPy and TensorFlow Probability—showing both algorithmic rigor and engineering discipline. His background blends hands-on backend refactoring, test automation and probabilistic ML, and he’s comfortable optimizing code for CPU and GPU contexts. Notably, he pairs product-driven ML work with community impact, mentoring newcomers in open source and writing about ML and Python.
7 years of coding experience
3 years of employment as a software developer
B.Tech, Information Technology, B.Tech, Information Technology at Charotar University of Science & Technology (CHARUSAT)
Github Skills (36)
sorting10
algorithms10
probabilistic-programming10
geometry10
pytest10
python10
data-science10
testing10
scikit10
pandas10
machine-learning10
c1110
indexing10
data-structure10
java10
Programming languages (6)
Github contributions (5)
cupy/cupy
Jan 2020 - Apr 2020
NumPy & SciPy for GPU
Role in this project:
Back-end Developer
Back-end DeveloperContributions:70 commits, 11 PRs, 128 comments in 3 months
Contributions summary:Rushabh primarily focused on refactoring and improving the CuPy library, a NumPy-compatible array library for GPU acceleration. They removed intermediate aliases, made requested changes, and replaced deprecated functions. Their contributions involved modifying core indexing and searching functionalities, as well as enhancing the norm calculation for matrices. The user also added support for zero-sized arrays and implemented the argwhere feature.
cudapythoncusolvergpunumpy
pandas-dev/pandas
Nov 2019 - Mar 2020
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 commits, 11 PRs, 131 comments in 3 months
Contributions summary:Rushabh primarily focused on improving the quality and reliability of the pandas library through the creation and modification of tests. This involved fixing mypy errors, adding tests for features like multiindex json, and ensuring correct behavior in edge cases related to CSV parsing. The contributions directly address potential bugs and maintain code correctness and API functionality by adding and modifying tests within the pandas test suite.
pythondatalabeled-datamanipulationdataframes
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