Nirav Patel
Student
Detroit Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolNirav Patel is a University of Michigan Ross graduate with six years of experience at the intersection of corporate strategy, technology, and sustainability, currently based in the Detroit metro area. He combines business training with hands-on machine learning and computer vision work—covering PyTorch and long egocentric video understanding research—to translate technical insights into strategic decisions. His background includes strategy and project management internships at Ford and Schreiber Foods, grounding his analytics in real-world operations. An active contributor to pandas testing and QA, he helps ensure reliability in one of the most widely used Python data libraries, reflecting a pragmatic attention to data quality. Nirav’s uncommon blend of business strategy, environmental interest, and deep learning research enables him to bridge product, data, and sustainability initiatives effectively.
6 years of coding experience
High School Diploma, High School Diploma at Grand Blanc Community SchoolsGlobal Semester Exchange, Global Semester Exchange at University of St.GallenDual Enrollment, Mathematics, Dual Enrollment, Mathematics at University of Michigan-FlintBachelor of Business Administration (BBA), Bachelor of Business Administration (BBA) at University of Michigan - Stephen M. Ross School of Business
Gujarati, Spanish
Github Skills (7)
testing10
pandas10
python10
test-automation10
data-analysis7
numpy7
data-science6
Programming languages (8)
Github contributions (5)
pandas-dev/pandas
Apr 2023 - Aug 2023
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:11 reviews, 8 PRs, 46 comments in 4 months
Contributions summary:Nirav primarily contributed to testing activities within the pandas library. Their work included writing and modifying tests for various functionalities, such as groupby operations with string dtypes, setitem operations with period dtypes, and the behavior of the apply function. They also addressed a bug related to the series sum function and its impact on the uint64 dtype. Their contributions focused on ensuring the accuracy and reliability of pandas' functionalities through comprehensive testing.
pythondatalabeled-datamanipulationdataframes
srkds/srkds
Feb 2022 - Dec 2023
Contributions:1 PR, 26 pushes, 1 branch in 1 year 11 months
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