Analysis of Public Opinion about Electric Vehicles on Twitter• Conducted sentiment analysis, time series modeling, and topic modeling on Twitter data related to EV cars, providing business insights into positive and negative opinions, trends over time, and topic clusters.• Predicted next quarter's sentiment scores for EV brands using time series modeling• Created Tableau dashboard and interactive visualization to report the findingsSubreddit Classification Using Supervised Machine Learning - Pet Food Brands on Reddit• Developed a model that uses natural language processing and machine learning to accurately predict the subreddit of a given Reddit post• Business insights into how users perceive different pet food brands and to identify any common positive or negative sentiments associated with these brands.• Developed an interactive Streamlit app for data analysis that provides users with insights and results.Forecasting Sales of a Store Using Time Series Regression Model (Kaggle competition)• Performed a thorough exploratory data analysis and data visualization to gain better business insights• Conducted time series regression model to forecast sales of a store for the following month

• Energy Production Data Analysis: Collected and analyzed data from renewable energy sources. Usedstatistical methods and time series analysis to understand energy production patterns, efficiency, andperformance metrics.• Predictive Modeling for Energy Forecasting to improve resource management: Developed predictivemodels that can forecast energy generation based on weather patterns, seasonal variations, and other relevant factors.• Energy Demand Analysis: Analyzed energy consumption patterns of clients or target regions to identifyopportunities for renewable energy integration and provided data insights that could lead torecommendations on the optimal sizing and placement of renewable energy systems.• Data Visualization and Reporting: Created several visually compelling reports and dashboards tocommunicate findings and insights to stakeholders, including clients, investors, and internal teams.

• Utilized data analysis techniques and visualization tools to identify trends and patterns in emissions data and communicate findings to clients, resulting in improved decisions and reduced environmental impact.• Conducted statistical modeling for air quality assessment of industries' emissions and its impacts on local air quality using CMAQ and WRF• Developed risk management plans for clients, including oil and gas refineries, by assessing hazards anddevising mitigation strategies to comply with regulations and minimize environmental impact