Data Science Case Studies
Price Optimization Model for Airbnb, which helps Airbnb hosts set the right price for their Airbnb listing and provides customers, the benefit of cost. This is a Regression Analysis problem.
Automotive aftermarket pricing analytics
Synthetic personal-lines insurance portfolio built as a governed digital twin, with dataset freezing, validation gates, and actuarial realism.
End-to-end Machine Learning project that predicts optimal product discount and estimates revenue impact using LightGBM and Streamlit.
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End-to-end machine learning project to predict whether hotel guests will cancel their booking. Includes pricing analysis and recommendations for increasing revenue and reducing cancellations.
End-to-end pricing analytics pipeline modeling gross-to-net optimizations, distributor discount structures, rebate ROI, and competitor gaps with interactive dashboard.
A PostgreSQL project exploring Zepto’s product inventory - cleaning and analyzing data to find category trends, top discounts, out-of-stock high-MRP items, and category-wise revenue.
Segment-level pricing diagnostics and forecasting for marketplace transaction data
Revenue optimization and pricing intelligence platform with elasticity analytics, profit optimization simulations, executive pricing dashboards, and strategic revenue insights.
Machine learning project for retail price optimization using Decision Tree Regressor and pricing analytics.
Identify the opportunities to improve upfront pricing precision in ride-hailing
Enterprise-grade decision support system for grain pricing and demand forecasting using machine learning, time-series forecasting, pricing scenario simulation, and business intelligence dashboards.
Pricing Analytics: Como os Dados Guiam Estratégias de Mercado de Cobre Trabalho apresentado para obtenção do título de especialista em Business Intelligence & Analytics na ECA-USP Pricing Analytics: How Data Guides Copper Market Strategies Work was presented to attain the Specialist in Business Intelligence & Analytics title at ECA-USP
Power BI dashboard analyzing car sales revenue and pricing drivers—make/seller performance, mileage vs price, condition buckets, transmission impact, MMR variance, and time trends.
Simulation study on reverse-engineering competitor tariffs. Comparing Active Learning, Simple Random Sampling and the Cube Method (Tillé & Deville).
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