I am a highly motivated Data Analyst with experience in data engineering, machine learning, and NLP-based chatbot development. I excel at extracting insights from data and presenting them through compelling visualizations, enabling informed decision-making for stakeholders. With a strong foundation in SQL, Python, Power BI and cloud-based technologies like Azure and AWS, I thrive on delivering impactful solutions.Professional Experience:Trainee Decision Scientist | Mu Sigma Inc.During my tenure at Mu Sigma, I worked on high-impact projects for Fortune 500 companies, using cutting-edge technologies to drive business outcomes.JohnGalt Reporting for Mars Inc.:- Utilized Azure Databricks, Azure Data Factory, and Power BI to process large-scale datasets.- Built dynamic dashboards to generate actionable insights, enabling strategic decision-making for Mars Inc.Improving NPS Score for Microsoft Teams:- Performed extensive Exploratory Data Analysis (EDA) on user feedback data.- Provided recommendations that directly contributed to enhancing customer experience on Microsoft Teams.>> Freelancing Projects:IMDB Movie Data Analysis:- Conducted in-depth analysis of the IMDB Movie Dataset, focusing on data cleaning, visualization, and exploratory data analysis.- Gained insights using Python libraries like Pandas, NumPy, and Matplotlib to uncover key trends in the movie industry.NLP-based Chatbot for IPL Dataset:- Developed an intelligent chatbot using AWS Lex, Lambda function, and S3 to generate responses based on IPL match data.- Built a simple webpage UI using HTML, CSS, and JavaScript to test the chatbot, integrating advanced NLP algorithms to provide accurate, conversational insights.Credit Risk Prediction:- Predicted customer credit failures using Random Forest Classifier, Support Vector Machine, and Logistic Regression.- Implemented data cleaning, plotting, and tuning optimal parameters for enhanced prediction accuracy in Jupyter Notebook.