Identifying Fraudulent Job Postings

This project focuses on identifying fraudulent job postings in the U.S. market using SQL and BigQuery. By analyzing a dataset from Kaggle detailing American job listings, we aim to distinguish deceptive ads from genuine ones, protecting job seekers from scams and potential financial losses.

Instacart Marketing Optimization

This project analyzes customer purchasing patterns on the Instacart online grocery platform, focusing on shopping times, product preferences, and department choices. Insights highlight Instacart's strength in delivering fresh goods promptly and the effectiveness of suggesting similar items to users.

Predicting Flight Delays

The project focuses on predicting flight delays of over 15 minutes at Chicago O'Hare International Airport. By analyzing variables such as airport operations, weather details, departure times, and airline data, we developed a classification model that minimizes prediction errors.

Spotlight on Spotify: Analyzing Global Music Streaming Trends

This project delves deep into the Spotify dataset to uncover global music trends, user preferences, and market dynamics using PySpark. Our exploration further branches into a comparison of Spotify with competitors like Apple Music. Additionally, we also used K means clustering for further insights.

Supply Chain Analytics

This Tableau-focused case study dives into real-world supply chain challenges, particularly in shipment and inventory management. Analyzed inefficiencies, using Tableau to visualize data and create dashboards that suggest business improvements.

Parkease (Design project)

This project’s mission is to create a user-friendly website that connects individuals in the United States who have available parking spaces with those seeking parking for a specific duration.

Analyzing Students' Mental Health in SQL

This project is a comprehensive analysis on the impact of studying abroad on student mental health using SQL queries to assess survey data from a Japanese university. This involved examining key factors like social connectedness and acculturative stress to predict depression likelihood in students.

Supply Chain and Applied Optimization

The project's objective is to develop an optimization model that minimizes overall wood procurement costs while ensuring smooth paper production and avoiding stockouts.