Sudeep Sidhu is a data engineer and Python developer with six years of experience building production data solutions and consulting for client success at firms like McKinsey and ZS. He combines a strong academic background in data science and big data engineering with hands-on Python contributions to the widely used SymPy project, where he enhanced physics and mechanics modules and implemented recursive velocity calculations. Recognized for on-time delivery and client satisfaction, he moves quickly from analysis to reliable implementations and mentors open-source contributors through programs like GSoC and SWoC. Comfortable bridging analytics, engineering, and client-facing roles, he thrives in dynamic teams and brings an analytical mindset plus a history of shipping well-tested, reusable library code.
6 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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