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Projects

Sentiment Analysis

Social Media Sentiment Analysis

Analysed comments across social platforms using NLP, K-Means clustering, and VADER to classify sentiment at scale with 92% positive signal accuracy.

Python NLTK VADER K-Means TF-IDF
X API Sentiment Pipeline

Twitter/X API Sentiment Pipeline

Built a real-time sentiment pipeline on live Twitter/X data using the v2 API with custom preprocessing, topic clustering, and trend detection.

Python X API v2 TextBlob Pandas
Churn Prediction

User Churn Prediction Model

End-to-end churn prediction using XGBoost and SHAP to identify at-risk fintech users — drove a 22% reduction in 90-day churn and ~₹8Cr in retained revenue.

Python XGBoost SHAP SQL Optuna
Marketing Mix Model

Bayesian Marketing Mix Model

Built a Bayesian MMM with adstock and saturation to measure true marketing ROI across 6 channels — improved blended efficiency by 31% and freed ₹3Cr in reallocated spend.

Python PyMC Bayesian statsmodels
Revenue Simulation

Revenue Simulation & Forecasting

Monte Carlo simulation engine that models 36-month revenue under uncertainty — surfaced churn as 2× the lever of acquisition, reshaping ₹30Cr+ annual planning.

Python Monte Carlo NumPy Plotly
Anomaly Detection

Payment Metrics Anomaly Detection

Real-time anomaly detection system for payment success rates, transaction volumes, and latency — reduced mean time to detect critical payment issues by 70%.

Python Isolation Forest statsmodels BigQuery Pub/Sub