This article reframes pricing as a negotiation rather than a prediction, showing how price emerges from tensions between product reality, market dynamics, and buyer behavior. It introduces negotiation-aware ML, value decomposition, and equilibrium modeling to build transparent, human-aligned pricing systems.

Multi-agent LLM simulations testing algorithmic collusion and coordination breakdown in oligopoly markets.

A Power BI-driven retail sales analysis project uncovering customer purchasing patterns, seasonal trends, product preferences, and revenue drivers using transactional data. Key insights and visuals support data-informed business decisions in inventory, pricing, and marketing strategies.

Dynamic Pricing is an application of data science that involves adjusting the prices of a product or service based on various factors in real time. It is used by companies to optimize revenue by setting flexible prices that respond to market demand, demographics, customer behaviour and competitor prices.

Business Experimentation: A/B Testing

This project includes the business plan of the Centaurus Racing Team's formula student car, completed as part of my bachelor studies.

This report presents a detailed analysis of an online sport retail business, focusing on revenue metrics, product performance, customer engagement, pricing strategy, brand analysis, and seasonal trends. Through Python and SQLite, various aspects of the business were examined and revealing key insights into revenue generation.

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

Backend service for the Price Optimization Tool — built with Django and Django REST Framework. Provides secure APIs for product management, demand forecasting, and price optimization with role-based authentication and filtering.

A web-based AI calculator helping SMEs (UMKM) accurately calculate Cost of Goods Sold (HPP/COGS) and profit margins using Python and Streamlit.

Adaptive pricing system for profit maximisation featuring frontend adapters, user modelling, APIs, and model evaluation.

Optimizing car insurance risk analysis with statistical modeling and machine learning to improve marketing strategy and premium pricing at AlphaCare Insurance Solutions.

A Dynamic Pricing framework integrating Monte Carlo simulations for demand uncertainty analysis and Response Surface Methodology (RSM) to optimize pricing strategies and maximize revenue.

Frontend interface for the Price Optimization Tool — built with React, TypeScript, and Vite. Features a clean, responsive UI for managing products, viewing demand forecasts, and exploring optimized pricing insights.

Vendor performance analysis integrating sales, purchase, and inventory data to optimize pricing, inventory, and supplier efficiency with SQL, Python, and Power BI.

A data-driven pricing optimization project using Excel and Python to increase revenue while adhering to business constraints.

Predictive analytics project for Airbnb pricing using multiple machine learning approaches

Data-driven SaaS pricing optimization using ML to maximize LTV/CAC ratios. Employs Random Forest, clustering, and elasticity analysis on 4,222 customers to recommend tiered pricing strategies that balance revenue growth with sustainable churn rates.

In this repository through advanced data analytics and market research assessed financial viability, customer behaviors, and market trends to form a strategic game acquisition recommendation. Process included market share simulation, cluster and factor analysis, GaborGranger pricing strategy, and customer segmentation.

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