Full-Stack .NET Developer
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Cars and Credit Master: Copart Auction Integration & Internal Tools
About the Project
Developed and maintained an internal web application that facilitated integration with Copart, a global provider of online vehicle auction services. The solution enabled Cars and Credit Master employees to seamlessly manage vehicle auctions and communications directly from their internal system.
- Automotive
Responsibilities
- Built a wizard-based UI that allowed users to list and manage vehicles on the Copart platform; - Integrated Copart API and email channels, capturing and displaying incoming requests and auction-related messages; - Implemented real-time user notifications for incoming messages and updates; - Enabled viewing of message details directly within the internal system; - Handled general maintenance tasks including bug fixes, UI/UX improvements, and database stored procedure updates;
Supply Chain Management System
About the Project
Contributed to the development of an enterprise-level application for managing supply chain operations. My primary focus was on building automated workflows for validating and updating shipment records to ensure accurate logistics data.
- Logistics
Responsibilities
- Implemented automatic validation logic for incoming shipments; - Developed update mechanisms for shipment statuses; - Worked with both backend and API layers to ensure reliable integration;
Skills & technologies
Crypto Coin Detection & Analysis System
About the Project
Developed a .NET-based application that integrated with Etherscan, TokenSniffer, Alchemy, and Basescan APIs to automatically detect all newly created tokens on the Ethereum network. In line with the client’s vision, the system used custom heuristics and real-time on-chain data to identify and filter out scam tokens, storing only legitimate tokens in a structured database. The system continuously monitored trading activity, tracked purchase patterns, and calculated the average holding period across multiple timeframes to evaluate investor sentiment and token volatility. A custom-trained LLM (Large Language Model) was also integrated to analyse market trends, historical price patterns, and social signals, providing predictive insights.
- Blockchain
- Cryptocurrency
- Machine Learning
Responsibilities
- Developed a .NET-based application to monitor and detect newly created tokens on the Ethereum network in real-time; - Integrated multiple blockchain APIs including Etherscan, TokenSniffer, Alchemy, and Basescan for comprehensive token data retrieval; - Designed and built a filtering system to separate legitimate tokens from fraudulent ones based on predefined criteria; - Configured secure database storage for validated tokens, ensuring only legitimate cryptocurrencies were cataloged;