**Kiran Sai Paleti**
(980) 382-0106 | ksai96371@gmail.com | LinkedIn | Git

**TECHNICAL SKILLS**
**Languages:** Java, Python, JavaScript, C#, C++, C, SQL, HTML5, CSS3
**Frameworks:** NodeJS, React, Spring Boot, MVC, OAuth 2, ExpressJS, Hibernate 4.0, Bootstrap
**Databases:** PostgreSQL, MongoDB, SQL Server
**Cloud Computing:** Amazon (AWS), Google Cloud
**Tools/IDEs:** Jupyter, Jira, PyCharm, Eclipse, Visual Studio, Git, MySQL Workbench, Postman

**WORK EXPERIENCE**
**McAfee, Bangalore, KA, IND**
*Software Development Engineer | Feb 2021 – Aug 2022*
- Designed and developed a full-stack web application using Agile methodology, covering SDLC phases.
- Converted legacy web pages to single-page applications with React, HTML5, Bootstrap, and CSS, improving performance by 25% using AJAX calls.
- Achieved 95%+ code coverage with JUnit in Test-Driven Development.
- Optimized stored procedures, resulting in 15% faster database performance.
- Troubleshot and fixed 50+ bugs, mentored 2 junior developers, and led a cross-functional team of 6 members.
- Proficient in CI/CD tools like Git and Microsoft Azure DevOps.

**UST Global, Bangalore, KA, IND**
*Software Engineer | Aug 2019 – Feb 2021*
- Developed enterprise-level Java applications using Spring and Hibernate, improving functionality by 30%.
- Configured dashboards, alarms, and ticketing for 2 services independently.
- Resolved high-severity customer issues and implemented bug fixes.

**EDUCATION**
**University of Cincinnati, Cincinnati, OH, USA**
*Master of Science in Information Technology | GPA: 4.0/4.0 | Jan 2023 – May 2024*
**Relevant Coursework:** Network Application Development, Algorithms and Data Structures, Mobile Application Development, System Integration, Software Secure Programming, Applied Databases

**PROJECTS**
**Personal Budget Web Application | Jan 2024 – Feb 2024**
*Tech Stack: Node.js, Express.js, MongoDB, React, HTML5, CSS3, JavaScript*
- Built and deployed a budget tracker on Heroku using MERN Stack.
- Implemented ChartJS for expense visualizations and budget forecasts.

**Client Segmentation for Banks Using Machine Learning | Mar 2024 – Apr 2024**
*Tech Stack: Python, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, Matplotlib, SQL, PostgreSQL*
- Developed an ML model improving marketing conversion by 20%.
- Preprocessed 1M+ client records for clustering algorithms.

**NodeJS TO-DO Web Application | Jan 2023 – Mar 2023**
*Tech Stack: Node.js, Express.js, MongoDB, HTML5, CSS3, JavaScript*
- Developed an event hosting and ticket booking web app.
- Secured passwords using SHA-512 encryption.

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