Worked as a Performance Tester using Apache JMeter at Larsen & Toubro. Gained extensive experience in performance testing for web applications, focusing on system stability, scalability, and responsiveness.

• Developed and executed performance test scripts to analyze application performance.
• Designed test scenarios to simulate high concurrent user load and stress conditions.
• Analyzed test results to identify performance bottlenecks and suggested improvements for better application responsiveness.
• Applied correlation and parameterization techniques to optimize test scripts.
• Prepared detailed test reports and provided recommendations for system improvement.

This internship enhanced my problem-solving and analytical skills, as well as my understanding of application performance optimization.

Completed a Data Analytics Virtual Internship, gaining hands-on experience in data preprocessing, visualization, and predictive analytics.

• Worked on the Bank Customer Churn Model project, analyzing customer data to predict churn using machine learning techniques.
• Performed data cleaning, feature engineering, and model evaluation to improve prediction accuracy.
• Visualized key insights using Python libraries such as Pandas and Matplotlib.
• Developed classification models and optimized hyperparameters for better performance.

Participated in a Data Science Virtual Internship, focusing on building predictive models and extracting insights from complex datasets.

• Developed the Hill & Valley Prediction project, predicting terrain types using machine learning classification algorithms.
• Implemented data preprocessing techniques such as normalization and handled missing values for accurate predictions.
• Trained and evaluated models using algorithms like Logistic Regression.
• Generated performance reports and visualizations to explain the model's results.