Data Scientist

Customer Growth Consulting Project for The Juice Laundry 

Project Consultant (March 2020 – April 2020)

• Analyzed >20k users’ data on retention, engagement, and customer flows using R to make recommendations on customer acquisition and retention strategies
• Designed 2 user engagement models for the brand; validated their product-market fit with data analytics

HR Analytics Consulting Project for Hilton 

Project Consultant (February 2020 – March 2020)

• Analyzed and extracted quantitative and qualitative information from >30k survey data using R, SPSS, and Tableau
• Quantified effectiveness of Hilton’s current employee retention strategies using logistic and multivariate regression

Kaggle NLP with Disaster Tweets Competition

• Cleaned ~10k data and performed exploratory data analysis using visualizations, frequency, and sentiment analysis
• Built 2 different Natural Language Processing prediction models using Logistic regression and SVM; achieved a mean-F score of 0.8

Kaggle House Prices Advanced Regression Techniques Competition

• Performed data cleaning, correlation analysis, and feature engineering to pre-process the data
• Built 2 different models using Lasso regression and Ridge regression, obtained a root mean squared error of 0.3