Blockchain Developer

Dhruv Varshney

India

About Candidate

Accomplished Blockchain Engineer with over 3 years of experience in smart contract development, DApp creation, and Web3 integration. Proven success with multiple Superteam bounties and winner of ETHIndia 2023, with expertise in Solidity, Ethereum, and Solana ecosystems.

Education

M
Mechanical Engineering and MSc. Economics 2020 - 2024
Birla Institute of Technology and Science, Pilani
W
Web3 Advanced Solidity Bootcamp 2024 -
Metana

Experiences

B
Blockchain Engineer

Freelancer: - Engineered sophisticated ERC20 tokens with features like god-mode, sanctions, token sales, and partial refunds, using Solidity and OpenZeppelin libraries. - Developed NFT contracts with traits and pictures, integrated with OpenSea and implementing ERC20 token-based minting mechanisms. - Created a full-stack dApp for ERC1155 token minting and forging, featuring MetaMask integration and real-time blockchain data display. - Implemented robust testing strategies with 100% line and branch coverage, and mutation testing using Sumo and Vertigo. - Developed real-time blockchain monitoring tools for tracking ERC20 token transfers, BASEFEE, and gas usage.

B
Blockchain Writer and Developer

Superteam India: - Authored 15+ in-depth technical articles on Solana development and research. - Contributed to key open-source Solana projects, including the Solana Cookbook and gib.work, improving documentation and functionality.

C
Chief Technical Officer, App Dev Lead

Oxon India: - Developed and deployed an innovative mobile application integrating multiple civic services in Gangapur, benefiting 200,000+ residents. - Secured support from PIEDS, ESRI, and the Rajasthan government, winning the InvEnt Award. - Led a cross-functional team of 20+ members, managing 5 elite developers from top institutions. - Launched the product on Google Play Store on March 3, 2022.

M
Machine Learning and Data Science Intern

TruckBook India: - Developed algorithms to analyze user behavior patterns from 10,000+ users. - Implemented web scraping techniques to improve job matching efficiency by extracting data from 500+ job postings. - Created a linear regression model using Scikit-learn to predict housing prices. - Engineered an image processing system using OpenCV and KNN to detect and match faces. - Automated data extraction from Yellow Pages using Selenium, improving market research efficiency.

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