I turn messy data into $36M business decisions. Currently pursuing my MS in Data Science at Northeastern, I'm passionate about solving real-world problems through data. My work has helped companies optimize everything from marketing campaigns to customer experiences.

I believe data science isn't just about algorithms, it's about impact. Whether I'm segmenting 30 million customers or building deep learning models for medical diagnosis, I focus on solutions that matter.

• Generated $36M in incremental revenue through ML-driven customer segmentation and personalized campaigns
• Increased customer walk-ins by 45% by identifying optimal promotional strategies during festive seasons
• Improved model performance from 0.71 to 0.83 AUC through advanced feature engineering
• Reduced decision-making time from days to hours with real-time dashboards and automated reporting
• Achieved 25% conversion improvement through rigorous A/B testing and statistical validation

• Diabetic Retinopathy Detection: 74% accuracy using EfficientNetB3 with Grad-CAM visualizations for clinical interpretability
• Hospital Readmission Prediction: ML solution analyzing 101K+ records to reduce readmissions

• Financial Chatbot BCG: Flask-based chatbot analyzing 10-K filings for Apple, Microsoft, and Tesla
• Credit Risk Management: End-to-end ML pipeline for loan default prediction

• Wildfire Detection CNN: Computer vision model for early wildfire detection with interpretable AI
• Boston 311 SQL Analysis: Advanced SQL case study optimizing city service responses

• Market Expansion Analysis: Identified $1.48M opportunities across 164 competition-free cities for Lugg
• TataIQ Retail Analytics: Tableau dashboards delivering C-suite insights

Languages: Python, SQL, R, JavaScript
ML/AI: TensorFlow, Keras, scikit-learn, XGBoost
Data: Pandas, NumPy, PySpark, Amazon Redshift
Visualization: Tableau, Power BI (Microsoft Certified), Plotly, Streamlit
Tools: Git, Docker, Flask, REST APIs

I'm a Microsoft-certified Power BI analyst who believes in democratizing data insights. When I'm not building models, you'll find me exploring Boston's tech scene or diving into the latest papers on interpretable AI.

• Advanced NLP techniques for financial document analysis
• MLOps best practices for production deployment
• Causal inference for better A/B testing

📫 Let's connect! I'm always excited to discuss data science, career opportunities, or that tricky pandas function:
Email | LinkedIn | Portfolio