I'm a motivated M.Tech student with a passion for data analysis and visualization, ready to tackle real-world challenges.
Discover my projects showcasing data analysis, visualization, and predictive modeling using tools like Tableau and Power BI.
Cleaned and processed datasets using Python (Pandas, NumPy) to ensure accurate business insights. Performed exploratory data analysis to identify customer preferences, content trends, and regional demand patterns. Built dashboards using Tableau/Power BI to present insights in a clear and decision-oriented manner. Strengthened analytical thinking and reporting skills through data-driven storytelling.
Developed a Random Forest model for predicting optimal solar installation locations. Performed data preprocessing, feature engineering, and statistical analysis to improve model accuracy. Enabled data-driven decision-making through predictive insights and visualization. Collaborated on project planning and execution in a fast-paced team environment.
I'm a motivated M.Tech student with a passion for data analysis and visualization, ready to tackle real-world challenges.
Energetic and adaptable Int. M.Tech student skilled in Python, SQL, Excel, and data visualization with hands-on experience in data analysis, dashboard creation, and business-oriented problem solving. Strong communication and analytical skills with the ability to work in fast-paced environments, manage multiple responsibilities, and support decision-making through actionable insights using Tableau, Power BI, and statistical techniques.
Experience
Research Extern 6 Extern
ROI Sponsorship Analysis 6 NY Racing Team · June 2026 6 Present
Summer Intern
Indian Oil Corporation Limited · May 2026 6 June 2026
Education
Vellore Institute of Technology
M.Tech CSE (Computational and Data Science)
Delhi Public School, Digboi
CBSE (Class XII)
Carmel School, Digboi
ICSE (Class X)
Skills
Cleaned and processed datasets using Python (Pandas, NumPy) to ensure accurate business insights. Performed exploratory data analysis to identify customer preferences, content trends, and regional demand patterns. Built dashboards using Tableau/Power BI to present insights in a clear and decision-oriented manner. Strengthened analytical thinking and reporting skills through data-driven storytelling.
Developed a Random Forest model for predicting optimal solar installation locations. Performed data preprocessing, feature engineering, and statistical analysis to improve model accuracy. Enabled data-driven decision-making through predictive insights and visualization. Collaborated on project planning and execution in a fast-paced team environment.
Analyzed pricing and booking trends using statistical techniques and visualization tools. Identified operational and seasonal factors affecting pricing and customer engagement. Created reports and visual dashboards to present actionable insights on customer preferences. Improved business analysis and problem-solving skills through real-world data interpretation.
Wrote SQL queries (joins, aggregations, filtering) to extract and analyze structured sales data. Generated reports to identify business trends and support operational decision-making. Improved query efficiency and strengthened analytical and reporting capabilities. Worked with structured datasets to extract meaningful customer and sales insights.
✅ Verified by Extern
During my externship with NY Racing, I gained insights into NASCAR's sponsorship economics and developed a targeted project scope for analytics. Through thorough research, I identified key sponsors and formulated a strategic roadmap to analyze their visibility and impact, setting a solid foundation for my project.
I analyzed a 20-season driver-sponsor partnership, summarized sponsorship tiers, estimated annual investment and activation tactics, and identified visibility indicators from the supplied case study.
Built a recommendation system using collaborative filtering after performing data wrangling and exploratory data analysis on the MovieLens dataset. Applied data mining techniques to generate personalized recommendations and visualized model performance using Mat-plotlib.
Forecasted unemployment trends using ARIMA, SARIMA, ARIMAX, and SARIMAX models. Performed data wrangling, statistical testing, feature preparation, and data visualization to evaluate forecasting performance.
Performed SQL-based data mining using joins, aggregations, subqueries, and window functions to analyze customer behavior and revenue trends. Created reports and dashboards that supported effective data storytelling and business decision-making.
