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MY PROJECTS

These contains a list of projects done by me on a personal level as well as within the academic scope at Boston University. 

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2024 U.S. Presidential Elections

Campaign Spending Analysis

Analyzed the USA Presidential Election Campaign Spending for 2024 by Each Party in Each State of the US.

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Clustering and T-Test Analysis of NYC Housing Market

Leveraged R to conduct K-means clustering, T-Test analysis, and descriptive statistics on NYC real estate data, uncovering key patterns in neighborhood pricing and sales trends.

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Business Consulting for Opening New Branch in Austin, Texas

Created Decision Tree, PESTEL, SWOT, Cost Analysis, 4-Ps of Marketing, What-If-Analysis, Optimization Analysis, Break-Even Point Analysis, Financial Ratios​​

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Marketing Analytics Project : Analysis of Lobster Land

Marketing Analysis and Strategy of Lobster Land, who is looking for a potential collaboration with Disney Land in Maine. 

Judge

Chicago Violations Analysis using Python

Analyzing trends, delays, and fines across wards from 2008–2024. Visualized with pandas, seaborn, and matplotlib.

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Digital Marketing Simulation Project - BUHI Corp (American Dream Line Bagpacks)

Utilized Paid Search Ads, Paid Display Ads, Ads Optimization, SEO, Keywords Optimization, Customer Segmentation, Targeting, Retargeting, A/B Testing, Web Analytics and Tracking. 

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New York Real Estate Business Analysis

Utilized Power BI and SQL to perform data cleaning, star schema modeling, and revenue and forecast analysis for Bayside, NYC, providing actionable insights for real estate investment decisions.

Credit Card Purchase

Credit Card Consumer

Data Analysis

Performed exploratory data analysis, handled multicollinearity, and built single and multiple linear regression models using Python (Pandas, Statsmodels, Scikit-learn) on Google Colab to predict consumer income.

Car Park

Car Sales Analysis using Looker Studio & Advanced Excel

The objective was to identify sales patterns, model profitability, recall trends, and customer sentiment across multiple car models and dealership networks to support strategic decision-making.

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Sentiment Analysis using NLP - For Amazon Customer Reviews

This project analyzes customer reviews on Amazon's product and develop a robust sentiment classification model. The goal was to extract insights from textual data, quantify customer sentiment, and accurately classify each review as positive, negative, or neutral using NLP and machine learning.

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