**NAGARJUNA BOLLA**
+1 8722585342
nagarjunareddybolla03@gmail.com
Chicago, IL, USA
LinkedIn | GitHub | Portfolio

### **EDUCATION**
**Illinois Institute of Technology**
*Master's, Computer Science* | Aug 2022 - May 2024 | GPA: 3.6
*Courses:* Machine Learning, Cloud Computing, Software Project Management, Natural Language Processing, Data Preparation & Analysis, Database Organization, Big Data Technologies

**Jawaharlal Nehru Technological University**
*Bachelor's, Electronics Engineering* | Aug 2017 - Jul 2021 | GPA: 3.5

### **EXPERIENCE**
**Shoptaki** (New York, U.S.)
*Software Developer (Intern)* | Feb 2024 - Present
- Developed backend logic for email/OTP verification and facial recognition for secure authentication.
- Designed algorithms to integrate facial data with codebase, enhancing security and data management.

**Deloitte** (Hyderabad, India)
*Software Engineer* | Aug 2021 - Jul 2022
- Built RESTful APIs using Node.js & Express.js for seamless frontend-backend interaction.
- Created 40+ test cases, improving feature enhancements and bug fixes by 5%.
- Implemented real-time Firebase database with AWS, reducing load time by 10%.

### **SKILLS**
**Programming Languages:** Java, Python, C, JavaScript, C#
**Frameworks/Libraries:** React.js, Django, OpenCV, Node.js, Flask, Express.js, REST API, Bootstrap, NumPy, SciPy, Pandas, Redux, Matplotlib, .NET, GraphQL, SpringBoot
**Databases/DevTools:** MongoDB, SQL, VS Code, Git, GitLab, Postman, Eclipse, PyCharm, Bash, PowerShell, Firebase
**Cloud/DevOps:** AWS (S3, EC2, IAM), Azure, Docker, CI/CD, Kubernetes

### **PROJECTS**
**Lyft Back-End Engineering Job Simulation** | [Git Source Code]
- Redesigned backend architecture using UML patterns, scaling for new features.
- Contributed to Lyft’s open-source codebase in JavaScript/Python with TDD.

**MERN Stack Web App with GenAI Chatbot** | [Git Source Code]
- Built a ReactJS site for a repair shop, replacing manual notes with MongoDB.
- Improved customer issue resolution by 20% using AI chatbots, boosting sales.

**Machine Learning in Software Project Management**
- Automated ML-OPS pipeline for code updates, issue tracking, and labeling.

**Network Intrusion Detection Using ML**
- Achieved 85% accuracy (vs. 81% baseline) with supervised/unsupervised models.

**House Price Prediction**
- Developed models with 90%+ accuracy using Kaggle housing data.

**Console User Management App** | [Git Source Code]

### **CERTIFICATIONS**
1. **AWS Course Certificate** (Udemy) – Taught by Paul Coady | [Link]

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