Rajesh Golthi

Dynamic Tester Intern at Krida Sports with a passion for quality assurance and a proven track record in manual testing. Leveraged Python and Agile methodologies to enhance game analytics, ensuring seamless user experiences. Excelled in cross-functional collaboration, driving continuous improvement and delivering actionable insights to elevate product quality.

• Flight ETA Change Prediction for Airline Operations, 02/01/26, 05/01/26, Python, Pandas, Scikit-learn, Machine Learning, Data Analytics, Integrated airline operations, weather, and airport datasets for predictive modeling., Performed data cleaning, feature engineering, and exploratory data analysis on large-scale flight data., Developed and evaluated regression and ensemble machine learning models to forecast post-takeoff ETA changes., Generated operational insights to support flight scheduling, resource planning, and decision-making.
• Predictive Fault Detection System for New Energy Vehicles (NEVs), 03/01/25, 06/01/25, Python, Decision Trees, Power BI, Agile Scrum, Preprocessed and analyzed vehicle sensor data to identify fault patterns and maintenance indicators., Developed a machine learning-based fault detection model for predictive maintenance applications., Created Power BI dashboards and visualizations to monitor vehicle health metrics., Collaborated in an Agile Scrum environment for sprint planning, model development, and project delivery.
• Donor Profit Optimization using Predictive Analytics, 03/01/25, 06/01/25, SAS Enterprise Miner, Neural Networks, Gradient Boosting, Predictive Analytics, Analyzed donor and demographic data to support data-driven fundraising strategies., Prepared and transformed datasets for classification and regression modeling., Developed predictive models to identify potential donors and estimate donation amounts., Evaluated model performance and delivered insights to improve campaign targeting and profitability.
• Road Accident Prediction Model, 08/01/22, Python, Machine Learning, Support Vector Machine (SVM), Data Analysis, Collected and analyzed traffic and environmental data sets to identify factors influencing road accidents., Performed data preprocessing, feature selection, and exploratory data analysis to improve data quality., Developed a Support Vector Machine (SVM) classification model to predict accident occurrence., Evaluated model performance and generated insights to support road safety and risk assessment initiatives.
• Rainfall Prediction Using ARIMA Model, 07/01/24, Python, ARIMA, Time Series Forecasting, Data Analytics, Analyzed historical weather and rainfall datasets to identify seasonal and trend patterns., Performed data cleaning, transformation, and time-series analysis for forecasting preparation., Developed an ARIMA-based forecasting model to predict future rainfall trends., Visualized forecast results and supported data-driven decision-making using predictive analytics.