Open Source Pricing & Packaging Infrastructure

Shiny app for Price Optimization using prophet and lme4 libraries for R.

Historical Sales Using Price Elasticity to determine customer responsiveness to future price changes

A REST API for computing local energy market (LEM) prices for a Renewable Energy Community (REC) that can promote the minimization of the members’ operation cost with energy.

A REST API for sizing and planning the operation of a Renewable Energy Community (REC) or Citizen Energy Community (CEC) that can promote the minimization of the members’ operation cost with energy.

Unlock profit potential with dynamic pricing! This machine learning project optimizes retail prices using regression trees, delving into price elasticity. Explore tools like Python, Pandas, and Matplotlib for robust analysis and decision-making in this data-driven pricing journey.

This repository includes a price optimization study about finding the best sales price for maximizing company revenues.

Projects on the way to completing the Data Analytics Diploma with honors at SAIT

Streamlit application to evaluate price elasticity of demand and optimize retail and combo menu pricing using regression models.

The main character energy for demand forecasting 🎬The algorithm ATE and left no crumbs 🍽️ Watch 295K sales records get sorted into the sickest price archetypes you've ever seen 👀

Syracuse University, Masters of Applied Data Science -SCM 651 Business Analytics

AI-powered auction bidding system using machine learning to optimize car purchase decisions. Combines VBA web scraping with Python decision trees to calculate optimal bid prices based on repair costs and market values.

Python CLI tool for searching and comparing cheap round-trip flights using Google Flights API, with advanced filtering, multi-date combinations, and intelligent caching for optimal travel booking

Price elasticity estimation per customer segment via log-log OLS regression. Revenue-maximising discount found using SciPy Brent's optimisation. Python · SciPy · Pandas

This project is a high-performance AI-Powered Dynamic Pricing & Inventory Intelligence Platform. It is designed to help e-commerce businesses maximize their profit margins and optimize stock levels using real-time market data and machine learning.

Pipeline de ML para otimização de preço de listings Airbnb no Rio de Janeiro. Demand curve estimation, FastAPI + Cloud Run, Airflow, MLflow, Evidently.

ML-based dynamic pricing system for retail optimization using Python, achieving 129% projected revenue increase

Causal ML pipeline for e-commerce dynamic pricing — Double Machine Learning for unbiased price elasticity, LightGBM demand forecasting (MAPE=0.418, R²=0.055), and a FastAPI pricing service delivering +30% revenue lift across 49,677 SKUs from 32M+ transactions.

Dynamic pricing engine: an XGBoost demand model plus a profit-maximizing optimizer, served via FastAPI with a versioned model registry. Evaluated honestly against a known demand function, capturing 89% of the oracle profit ceiling.

Applied ML — OTTO co-visitation recommender + price optimization on M5 (Thompson sampling, LP).