Entry-Level Full-Stack Developer - React, Node

BHARATH CHANDRA KAPARAPU

+91-949******* E-mail LinkedIn

PROFILE SUMMARY

Motivated Computer Science graduate seeking an entry-level software engineering role to apply strong front-end and back-end

development skills. Proficient in HTML and programming fundamentals with a focus on implementing clean, efficient, and scalable

code following best practices. Eager to collaborate with cross-functional teams and contribute to innovative solutions in a fast-

paced development environment. Possess strong communication skills, problem-solving ability, and a commitment to continuous

learning and improvement. Looking to implement impactful software solutions that enhance user experience and support

organizational goals.

PROJECTS

AI Hub – Multi-AI SaaS Chat Platform – GitHub-link

Tech Stack: React.js, Node.js, Express.js, MongoDB, JWT, Tailwind CSS, REST APIs

• Developed a full-stack multi-AI chat platform integrating GPT, Claude, and Gemini with smart model routing.

• Implemented JWT authentication, usage tracking, and tier-based pricing, supporting 3 subscription plans with 200–10K

monthly requests.

• Built REST APIs and MongoDB conversation storage enabling real-time chat, history management, and scalable request

handling.

Real-Time Order Processing System using Apache Kafka – GitHub-link

Tech Stack: Apache Kafka, Python, Kafka Producer & Consumer APIs, KRaft, REST API, JSON, Docker

• Developed a real-time order event streaming system using Apache Kafka to capture and process order transactions

with producer–consumer architecture.

• Implemented Python-based consumers for stream processing, filtering, and aggregation, enabling asynchronous and

scalable data pipelines.

• Configured Kafka topics with partitioning and offset handling to ensure fault tolerance, high throughput, and reliable

message delivery across distributed services.

Financial Fraud Detection

Tech Stack: Python, Scikit-learn, XGBoost, Pandas, SHAP

• Built a financial fraud detection pipeline using Logistic Regression and XGBoost, achieving ~98% classification accuracy

and reducing false positives by ~25%.

• Addressed severe class imbalance with SMOTE and ADASYN, improving minority-class recall by ~30% and boosting

overall model robustness.

• Implemented SHAP-based feature explainability to interpret predictions, identifying top 5–10 key fraud indicators and

enhancing stakeholder trust in model decisions.

TECHNICAL SKILLS

• Languages : Python, JavaScript.

• Frontend : HTML5, CSS3, Tailwind CSS, React.

• Backend : Node.js, Express.js, RESTful APIs.

• Databases : MySQL, MongoDB.

• Tools : Git, GitHub, Docker, Postman, Kafka.

SOFT SKILLS

Critical Thinking Communication Time management Active listener Flexibility Adaptability Leadership.

CERTIFICATIONS

• Python Programming: Mastering the Essentials — Scaler Topics

• Database Management Systems — Udemy

EDUCATION

Bachelor of Technology (B. Tech) in Computer Science and Engineering 2021 – 2025

Vasireddy Venkatadri Institute of Technology CGPA: 7.56

Intermediate (Class XII) 2019 – 2021

Sri Chaitanya Junior College Percentage:83.0%

Secondary School (Class X) 2019

Live School CGPA: 9.5

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