Sudeep Sidhu is a Delhi-based data engineer with five years of experience combining Python development, data engineering, and client-facing technology consulting, currently driving client success at McKinsey & Company. He has practical delivery experience from ZS and startup roles, and holds an MS in Data Science plus an executive postgraduate credential in Big Data Engineering. An active open-source contributor and GSoC alumnus, he made notable backend contributions to the widely used SymPy computer algebra system—adding recursive velocity calculations and refining joints APIs in the physics/mechanics modules. Recognized with performance awards for client satisfaction and on-time delivery, he also mentors emerging developers, reflecting a collaborative, fast-learning approach to solving complex production problems.
5 years of coding experience
3 years of employment as a software developer
Executive Post Graduate Programme, Big Data Engineering and Analytics, Executive Post Graduate Programme, Big Data Engineering and Analytics at International Institute of Information Technology Bangalore
Bachelor of Technology - BTech, Information Technology, 8.9, Bachelor of Technology - BTech, Information Technology, 8.9 at Maharaja Surajmal Institute Of Technology
Master of Science - MS, Data Science, Master of Science - MS, Data Science at Liverpool John Moores University
Contributions:398 reviews, 374 commits, 149 PRs in 1 year 7 months
Contributions summary:Sudeep's commits primarily focus on improving the SymPy library's physics and mechanics modules. They added new functionality for calculating velocity, including recursive velocity calculations, and implemented tests to ensure correctness. Moreover, they finalized the joints' abstract base class and updated the APIs for various functions.
Contributions:8 reviews, 33 PRs, 32 pushes in 7 months
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