Pratap Vardhan
Principal Data Scientist
India
Summary
👤
Senior🎓
Top SchoolPratap Vardhan is a Principal Data Scientist with 12 years of experience building full-stack data science products that turn messy data into compelling, shareable stories. Currently at Khan Academy and as the founder of Stats of India, he designs and deploys scalable ML systems, reusable data components, and user-facing visual interfaces that help non-technical audiences make decisions. His open-source contributions span notable projects like Bokeh and Altair—where he improved examples and performance—and financial and image libraries (ffn, scikit-image), reflecting deep practical expertise in visualization, testing, and code quality. He has bridged research and industry roles from IIT Bombay and Thomson Reuters to startups and consultancies, often translating domain problems into production-ready analytics. Notably, his work emphasizes clean data pipelines and reproducible examples (e.g., modernizing dataframe usage in Bokeh) that make advanced techniques accessible. Based in India, he combines academic rigor with product-minded engineering to ship impactful data experiences.
12 years of coding experience
14 years of employment as a software developer
School, School at P. Obul Reddy Public School, HyderabadB.Tech Electronics & Communications, B.Tech Electronics & Communications at Maulana Azad National Institute of Technology
Github Skills (37)
data-visualizations10
unit-testing10
data-analysis10
bokeh10
python10
jupyter10
data-science10
testing10
pandas10
nltk10
data-visualisation10
scikit-image10
numpy10
vi10
financial-analysis10
Programming languages (7)
Github contributions (5)
pmorissette/ffn
Jan 2018 - Aug 2018
ffn - a financial function library for Python
Role in this project:
Data Scientist
Data ScientistContributions:7 commits, 5 PRs in 6 months
Contributions summary:Pratap primarily contributed to refactoring and optimizing the `ffn` library, focusing on improving code efficiency and readability. Their work involved replacing deprecated functions with built-in alternatives and simplifying code structures. The user also made several improvements to the testing suite, including adding tests and refining existing ones. These contributions enhanced the library's performance and maintainability, particularly in the context of financial function calculations.
financialpythonfunction-libraryfinancial-dataquantitative-finance
scikit-image/scikit-image
Oct 2014 - Nov 2015
Image processing in Python
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:19 commits, 2 PRs, 8 comments in 1 year 1 month
Contributions summary:Pratap primarily contributed to improving the testing infrastructure and adding comprehensive tests for morphological structuring elements within the scikit-image library. This involved writing new test functions, adding docstrings to existing tests, and correcting some minor bugs that caused testing failures. Their work included adding tests for the cube and ellipse structuring elements and fixing dtype mismatches.
image-processingpythoncomputer-visionimage
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.