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Click here or scroll down to respond to this candidateCandidate's Name
Street Address -705-2991 EMAIL AVAILABLE:com / /github.https://com/www.Candidate's Name LINKEDIN LINK AVAILABLE EducationRutgers University, New Brunswick NJBachelor of Science in Computer Science and Data Science Aug. Street Address May 2026 Relevant Courses: Data Structures (Java), Discrete Structures, Computer Architecture (C), Systems Programming (C), Design and Algorithms, Data Management for Data Science (Python, Numpy, Pandas, SQL), Data 101 (R, R Studio) GPA: 3.9 out of 4Technical SkillsLanguages: Java, Python, HTML, CSS, JavaScript, React, MySQL, SQL, Git, C, R Frameworks/Developer Tools: Android Studio, Unity, Docker, Kubernetes, AWS(EC2) Platforms: Salesforce Commerce CloudExperienceAvis Budget Group May 2024 August 2024Software Engineer Intern Collaborated with cross-functional teams of 8 members to design and implement scalable BFF modules for a new consumer product, enhancing the applications performance by 13%. Participated in 10+ code reviews to ensure quality by incorporating tools like Bitbucket cloud and aided the SDLC through feedback from about 15 customer sessions Developed dynamic UIs with React/React Native, boosting user engagement by 20% across web/mobile platforms Utilized NestJS to build maintainable backend services, providing robust API endpoints for frontend consumption. Implemented CI/CD pipelines using Concourse, automating the build, test, and deployment process, reducing deployment time by 16% and achieving 99% reliability in software delivery Deployed/managed Kubernetes application containers, achieving high availability and scalability for the user base. RafterOne July 2023 August 2023Salesforce Intern Trained extensively on Commercial Cloud. Developed a fully functional storefront with foundational features like inventory management, easy application of pricing and discount to manage products leveraging the latest flows and apex coding as needed Developed reports and dashboards to support product management. ProjectsLazyTrader Python, Flask, Machine Learning, AWS, Algorithmic Trading, React, SQL Developed a live, automated 24/7 Python trading bot, leveraging multi-threading to stream prices and execute real-time trades. Built a high-performance back-testing system for various algorithmic trading techniques (Keltner Channels, Bollinger Bands, MACD, RSI), simulating thousands of trades across multiple instruments over 6 years. System is coupled with a full-stack monitoring app, and interactive UI (React, Flask API) for dynamic reporting. Applied machine learning techniques (Mean Reversion, Regression, Classification) to optimize strategies. Utilized MySQL for data storage and management of trading information. Created RESTful APIs with Flask for real-time access to technicals, prices, market sentiments, and bot status. Scraped live economic data and market headlines for strategic input. Deployed on AWS EC2 with comprehensive logging for reliability and scaling. Linux Shell C Designed and implemented a custom Linux shell, providing interactive and batch modes for executing and managing a sequence of shell commands Gained expertise in POSIX stream IO, directory management, and advanced process control Utilized system calls for implementing redirection and piping between processes, enhancing command functionality Developed features including wildcard pattern matching, input/output redirection, and conditional command execution, ensuring robust and efficient shell operations |
