Projects
Real-world data science projects demonstrating machine learning, analytics, and problem-solving skills
Customer Churn Prediction
Built a predictive model to identify customers at risk of churning, helping businesses retain high-value customers.
Impact: Attained an F1-score of 0.84, correctly identifying 92% of high-risk customers.
What I Learned: Hyperparameter tuning, handling imbalanced datasets, and implementing explainable AI techniques to make model decisions transparent.
Airbnb Price Prediction
Developed a regression model to predict Airbnb listing prices based on features like location, amenities, and reviews.
Impact: Achieved 87% accuracy and reduced prediction error by 12% through advanced feature engineering.
What I Learned: Feature engineering techniques, correlation analysis, one-hot encoding, and feature importance evaluation for model interpretability.
IMDb Sentiment Analysis
Created an NLP model to classify movie reviews as positive or negative, supporting content moderation and user insights.
Impact: Classified 50,000+ reviews with 89% accuracy using TFIDF vectorization and logistic regression.
What I Learned: Text preprocessing, TFIDF vectorization, sentiment classification, and visualizing sentiment trends across different movie genres.
Airline Performance Dashboard
Built an interactive Power BI dashboard to track airline operations, including delays, cancellations, and performance metrics.
Impact: Analysed 500,000+ flight records, creating DAX-based KPIs that enable quick operational decision-making.
What I Learned: Power BI dashboard design, DAX formulas for custom KPIs, data modeling, and creating actionable insights for stakeholders.
KPMG Customer Segmentation
Segmented customers based on purchasing behavior using Excel to improve targeted marketing strategies.
Impact: Segmented 1,000+ customers, boosting targeted marketing efficiency by 15%.
What I Learned: Customer segmentation techniques, PivotTables for interactive analysis, and translating data insights into marketing recommendations.
Walmart Sales Analysis
Analyzed Walmart sales data using advanced SQL queries to uncover product, branch, and seasonal trends.
Impact: Delivered insights on top-performing branches and products to support operational decisions.
What I Learned: Advanced SQL techniques including joins, subqueries, window functions, and aggregations for comprehensive sales analysis.
Interested in Collaborating?
I'm always open to discussing data science projects, learning opportunities, or collaborations.