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Trijesh Kondapuram

@trijeshkondapuram

Data Science Intern at AtliQ Technologies who achieved 92.26% accuracy with an XGBoost model and deployed it in a Streamlit app.

India

Message

At AtliQ Technologies, I analyzed campaign performance across two campaigns and prepared customer behavior data for a beverage price-range classification project. I evaluated six machine learning models on 7,489 test records; XGBoost achieved 92.26% accuracy, and I tracked experiments with MLflow before delivering the model through a Streamlit app.

In my projects, I built a credit-risk model with ROC-AUC above 0.90 and launched a Streamlit app tested by more than 40 users. I also developed an agentic AI system for HR workflows and a health insurance premium prediction app.

Experience

Work history, roles, and key accomplishments

Data Science Intern

AtliQ Technologies

Sep 2026 - Oct 2026 (1 month)

Analyzed campaign performance using Python and Pandas to evaluate marketing KPIs. Designed features and evaluated ML models, achieving 92.26% accuracy with XGBoost and delivering via a Streamlit app.

Python Pandas Machine Learning XGBoost MLFlow Streamlit