Gurumeher Sawhney
AI Engineer at Tiger Global
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolGurumeher Sawhney is an AI engineer with nine years of experience building production ML systems and data-driven products across Amazon, healthcare AI at Vital, consulting at Bain, and now Tiger Global in New York. He blends software engineering rigor from his SDE days with applied machine learning and product-focused consulting, frequently translating research-grade models into operational pipelines. His open-source contributions include algorithmic trading tutorials and documentation for QuantConnect, reflecting a knack for clear technical communication and reproducible workflows. Comfortable across back-end systems, model development, and stakeholder-facing delivery, he has a track record of improving outcomes in regulated and high-scale environments. Gurumeher’s background in computer science and economics informs a pragmatic approach to problem framing and trade-offs, and he often surfaces non-obvious operational constraints early in projects.
9 years of coding experience
4 years of employment as a software developer
B.A. Computer Science Economics (Theory), B.A. Computer Science Economics (Theory) at New York University
Spanish, Punjabi, Hindi, English
Github Skills (18)
markdown10
develop10
python10
finance10
strategy-pattern10
quantconnect10
markdown-it10
statistical-models10
jupyter-notebook10
algorithmic-trading10
modeling10
documentation10
backtest9
backtesting9
php7
Programming languages (5)
Github contributions (5)
QuantConnect/Tutorials
Jul 2018 - Aug 2018
Jupyter notebook tutorials from QuantConnect website for Python, Finance and LEAN.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:12 commits, 6 PRs, 2 comments in 21 days
Contributions summary:Gurumeher primarily focused on adding and updating tutorials within the QuantConnect tutorial library, which includes financial and algorithmic trading strategies. They implemented new trading algorithms and updated existing ones, including the "Turn of the Month" and "Paired Switching" strategies. The user also made changes to the strategy library's structure by updating indexes, demonstrating experience with both back-end algorithm development and front-end documentation and presentation through the tutorial format.
pythonquantconnectjupyter-notebooknotebookjupyter
QuantConnect/Documentation
Jul 2018 - Aug 2018
QuantConnect Wiki Style Documentation Behind QuantConnect
Role in this project:Technical Writer
Technical WriterContributions:9 commits, 7 PRs, 1 comment in 1 month
Contributions summary:Gurumeher primarily contributed to the documentation within the `quantconnect/documentation` repository. Their commits focused on updating and adding content to the documentation regarding time zones for various data sources like GDAX, OANDA, and futures data. They also updated documentation related to configuring universe securities and provided links to learning resources. The user's work ensured the documentation remained accurate and provided valuable insights to users of the platform.
wikiquantconnect
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