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Projects

Here are some of the projects I’ve worked on 

Predictive Analysis & Recommendation System 
Course Social Media & Text Analytics

Data Scientist

  • Built a content-based movie recommendation pipeline in Python using Scikit-learn’s TF-IDF vectorizer and cosine similarity on 9K+ movies, designed to personalize movie suggestions.

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  • Built a sentiment-classification pipeline using TF-IDF feature extraction and Logistic Regression in Python (Scikit-learn) on 100K+ movie reviews, achieving ~92% cross-validated accuracy in predicting whether a movie received a high rating.

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Rochester, New York

Feb 2024 – Apr 2024

Profit Optimization & Production Modeling 
Course Spreadsheet Modeling

Data Analyst

  • Developed a linear programming model in Excel that identified the optimal production mix for MNC, increasing total variable margin to $2,839.76 within machine-time, material, and demand constraints.

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  • Conducted sensitivity analysis to recommend optimal product reductions and resource allocations, such as reducing Cluster chocolate production and expanding packaging machine capacity, enhancing MNC’s decision-making and profit optimization.

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Rochester, New York

Jan 2024 - Mar 2024

Data Analytics & Design  Cobblestone Learning Centers

Marketing Analyst

  • Analyzed A/B testing data from 9K+ students using quasi-experimental design and multivariate regression in R, identifying programs that improved grades by up to 5% with 90–95% confidence.
     

  • Segmented 2K+ students using k-means clustering on an 11-question motivation survey, creating 4 data-driven audience profiles that personalized advertising campaigns.
     

  • Developed AI-powered learning tools using generative AI (LLMs) to deliver adaptive and engaging learning experiences.

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Rochester, New York

Oct 2023 – Dec 2023

RIT Business Analytics Case Competition
Global Hotels and Resorts (GHR)

Business Analyst

  • Developed predictive models using correlation analysis, multivariate regression, and MARS algorithms; applied BIC for model selection to uncover 8 key insights on revenue optimization, customer behavior, and seasonal demand patterns.

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  • Led a cross-functional 5-member team in analyzing 50K+ customer transaction records, earning a 4.5/5 overall score among 50+ international teams.

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Rochester, New York

Oct 2023 – Dec 2023

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