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Lucky Rangi

@luckyrangi

Data Science Intern at Celebal Technologies who improved fraud detection model accuracy by 15% and built deployable ML APIs.

India

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What I'm looking for

I'm actively expanding into Generative AI, agentic systems, and cloud platforms, building on my experience developing end-to-end AI/ML pipelines and production-ready APIs.

At Celebal Technologies, I applied data preprocessing and feature engineering to build predictive models for fraud detection and customer segmentation. My work improved model accuracy by 15% and reduced the fraud detection false positive rate by 20%.

For my Smart Loan Default Prediction System project, I built an end-to-end machine learning pipeline and developed REST APIs for real-time loan risk prediction. I containerized the application with Docker and deployed it via Kubernetes on Render.

At Mission Minded Foundation, I developed responsive, interactive web pages and implemented UI components with the design team. Code optimization improved cross-browser compatibility and reduced page load time by 10%.

At PIET AICTE IDEA LAB, I built a real-time monitoring and alert system using Arduino, ESP32, and sensors. I’m expanding my foundations in AI agents, orchestration, and LLM concepts while exploring Generative AI and cloud platforms.

Experience

Work history, roles, and key accomplishments

Data Science Intern

Celebal Technologies

Jun 2025 - Aug 2025 (2 months)

Applied data preprocessing, feature engineering, and machine learning techniques on real-world datasets to build predictive models for fraud detection and customer segmentation, improving model accuracy by 15%. Built and evaluated classification and regression models using Python, reducing the false positive rate in fraud detection by 20%.

Python scikit learn Pandas NumPy Machine Learning Feature Engineering EDA Classification regression Fraud Detection Customer Segmentation

Frontend Development Intern

Mission Minded Foundation

Aug 2024 - Sep 2024 (1 month)

Developed 5+ responsive, interactive web pages using HTML, CSS, and JavaScript, improving cross-browser compatibility across Chrome, Firefox, and Edge. Collaborated with the design team to implement UI components, reducing page load time by 10% through code optimization.

HTML CSS JavaScript Responsive Design cross browser compatibility UI Components Optimization

IoT Intern

PIET AICTE IDEA LAB

Aug 2023 - Aug 2023 (0 months)

Built a real-time monitoring and alert system with Arduino and ESP32, reducing detection delay to under 2 seconds. Integrated temperature, motion, and gas sensors for 24/7 automated monitoring, achieving 98% uptime on a live prototype.

Arduino ESP32 IoT Sensor Integration Real time Monitoring Alert Systems