I am an enthusiastic postgraduate student with a positive attitude towards work. I have about a year of experience working as an IT Service Desk Analyst at ESP Global Services, a multinational company. In this role, I scheduled and coordinated engineering resources, troubleshooting hardware and software issues, handling network issues, and providing remote support to clients. I am skilled in using ServiceNow and ensuring end-to-end support within SLA.
Additionally, I have worked on two notable projects during my academic journey. In the Telecom Churn Prediction Project, I analyzed telecom customer churn using advanced machine learning models. I conducted data cleaning, exploratory data analysis, and applied predictive analytics to identify key drivers of customer churn. I developed a model to predict customer retention rates, which enhanced strategic decision-making.
In the Protein Localization Data Classification project, I executed the classification of protein strains in E. coli using machine learning. I employed Naive Bayes and Logistic Regression models for predictive analysis, implemented data pre-processing techniques, and created visualizations such as ROC curves to evaluate model performance. These projects have showcased my proficiency in Python, SQL, Pandas, NumPy, Matplotlib, Seaborn, NLTK, and GitHub.
