Welcome to my data science portfolio! I am a Data Scientist with 4+ years of experience in building data-driven solutions to solve complex business problems.
- Goal: Classify high-traffic recipes to improve the product by increasing site traffic.
- Tech Stack: Python, Logistic Regression, Random Forest, Feature Engineering, Data Normalization
- Results: Achieved an AUROC of 0.902 with a Logistic Regression model and implemented a Key Performance Indicator (KPI) to maintain an 84% High Traffic Conversion Rate.
- Details: Notebook
- Goal: Classify facial images into their corresponding seasonal tones based on color theory.
- Tech Stack: Python, Deep Learning, Neural Networks, Custom Triplet Loss, Computer Vision
- Results: Achieved 74.47% accuracy on the initial dataset, with potential for improvement using a larger and more representative dataset.
- Details: Notebook
- Goal: Minimize Netflix user’s browsing time by optimizing Match Score, Tile Size, Preview Length, and Preview Type.
- Tech Stack: Python, A/B Testing, Factorial Design, F-tests, Partial F-tests
- Results: Reduced browsing time to an average of 10.02 minutes with a 95% confidence interval.
- Details: Notebook
- Goal: Predict the conversion rate for adding non-medical items to the cart and evaluate the potential impact of a proposed feature change on the e-commerce platform.
- Tech Stack: SQL, Python, Time Series Analysis, Augmented Dickey-Fuller Test
- Results: Forecast shows conversion rate reaching 20% in 3 months, with an upward trend correlated to revenue gains. The proposed feature change by the Product Team could accelerate this trend by increasing visibility of non-medical items during checkout.
- Details: Report
- Statistics - MSDS
- Advanced Machine Learning - MSDS
- Deep Learning - MSDS
- Experiments in Data Science - MSDS
- Time Series - MSDS
Feel free to reach out to me for collaboration or inquiries!