I'm a Data Scientist with 6+ years of analytics experience, building machine learning projects to solve real business problems.
| Project | Description | Tools |
|---|---|---|
| Churn Prediction | Predicts telecom customer churn using XGBoost and SMOTE. ROC AUC: 0.83 | Python, XGBoost, scikit-learn |
| A/B Testing Framework | End-to-end experiment analysis for Microsoft Teams onboarding. $600K revenue impact identified | Python, scipy, statsmodels |
| NLP Sentiment Analysis | Classifies Microsoft product reviews as positive, neutral, or negative. Identified Azure as highest priority product for sentiment improvement | Python, NLTK, TF-IDF, scikit-learn |
| Azure ML Pipeline | End-to-end ML pipeline trained on Azure with real-time FastAPI prediction endpoint | Python, Azure ML, XGBoost, FastAPI |
| RAG Support Assistant | AI-powered Microsoft product support assistant using RAG and Azure OpenAI GPT-4o. Prevents hallucinations by grounding responses in retrieved documentation | Python, Azure OpenAI, GPT-4o, TF-IDF |
Languages: Python, SQL, R
ML & AI: scikit-learn, XGBoost, NLTK, imbalanced-learn, LLMs, RAG
Generative AI: Azure OpenAI, GPT, Prompt Engineering
Experimentation: A/B Testing, Power Analysis, Hypothesis Testing
Cloud: Microsoft Azure, Azure ML, Azure OpenAI, AWS, Databricks, GCP
MLOps: FastAPI, REST APIs, Model Deployment, Model Registry
Tools: Jupyter, Git, pandas, matplotlib, seaborn, Power BI, Tableau