Tushar Sharma
Data Scientist
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTushar Sharma is a data scientist with 13 years of experience building scalable B2B SaaS products and data-driven services, now applying his skills at Lyft in San Francisco. He blends statistical modeling, forecasting, and A/B testing with practical engineering chops in Python and SQL to turn complex data into actionable product decisions. At Salesforce he moved from intern prototyping multivariate time-series and 3D bin-packing solutions to full engineering roles, demonstrating an ability to take models from proof-of-concept into production. An active open-source contributor, he improved the Rake-NLTK library by adding multilingual support, performance optimizations, and configurable phrase extraction limits. Known for strong data storytelling and visualization, he pairs rigorous analysis with clear communication to influence stakeholders. A self-described philomath, he continuously pursues new techniques at the intersection of ML, systems, and product analytics.
13 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at University of California, Berkeley
Github Skills (4)
algorithm10
nltk10
python10
documentation9
Programming languages (7)
Github contributions (5)
csurfer/rake-nltk
Jan 2017 - Sep 2021
Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:68 commits, 23 PRs, 71 pushes in 4 years 8 months
Contributions summary:Tushar primarily focused on improving and maintaining the Rake-NLTK library's core functionality. Their contributions included adding support for multiple languages, which involved modifying the `rake.py` and `__init__.py` files. The user also incorporated enhancements, such as including control over the maximum and minimum words in a phrase, alongside code cleanup and speed optimizations. Further, the user updated documentation within the `README.rst`, reflecting improvements in functionality and usage.
keyword-extractionnltkpythontext-mining
csurfer/dot-files
Jun 2016 - Aug 2019
Contributions:34 commits, 49 pushes, 1 branch in 3 years 2 months
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