Analyze product data for an online sports retail company to optimize revenue.

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.

Applying product segmentation, demand forecasting, and revenue optimization to increase online retailer revenue

Understanding customer buying patterns and retention behavior.

Analysis of KMS' Order data from 2009-2012. Includes pivot tables, charts, and insights on sales, regions, customer profitability, and shipping costs. Provides recommendations to optimize operations and enhance revenue for Kultra Mega Stores.

Comprehensive customer acquisition systems covering modern lead generation, conversion optimization, and customer onboarding methodologies. Build sustainable customer acquisition processes.

Optimización de ingresos e-commerce mediante priorización ICE/RICE y análisis de Tests A/B. Implementación robusta con Mann-Whitney U, corrección de Bonferroni y filtrado técnico de outliers (P96/P97) para identificar el impacto real en conversión. Desarrollado con Python y Pandas 3.0 (PyArrow backend) para procesamiento de alto rendimiento.

From data engineering to behavioral clustering, predictive modeling, and a live BI dashboard.

An enterprise-grade system that automatically discovers open tenders, analyzes RFP requirements, generates competitive proposals, and submits responses to maximize revenue through automated bid management.

🔔 Receive Apple App Store revenue notifications in real-time on your device with RevenueBell, a lightweight Cloudflare Worker script.

An alternative to Nomis solutions on e-Cars case through Logistic Regression with Lasso regularization

Analyzed hotel booking cancellations, implemented dynamic pricing for a 15% reduction, initiated targeted marketing for 12% rise in peak month bookings, and optimized booking sources. Enhanced revenue and strategy through data-driven insights.

Healthcare Operations Analyst | Transforming hospital data into $427K revenue recovery opportunities through Python analytics and interactive Streamlit dashboards. Specialized in predictive modeling, operational optimization, and executive reporting for healthcare systems.

Analyzed hotel booking cancellations, implemented dynamic pricing for a 15% reduction, initiated targeted marketing for 12% rise in peak month bookings, and optimized booking sources. Enhanced revenue and strategy through data-driven insights.

🏨 Dynamic Pricing Dashboard for Hotel Revenue Optimization - AI-driven pricing strategies with machine learning models and interactive visualizations

SQL and Python-powered analysis of airline data to uncover insights on occupancy rates, revenue performance, and pricing strategies for improved profitability.

A falta de traducción a inglés y piloto para Negocio

Power BI dashboard analyzing 119k hotel bookings to validate revenue hypotheses. Identified €5M opportunity in family segment, 2.4x cancellation risk for early bookings, and 72% summer revenue concentration.

IT contains data analysis and visualizations aimed at improving a landscaping company's revenue and customer satisfaction. The project addresses two sub-goals: increasing revenue and improving customer satisfaction. Four visualizations are provided, each contributing insights toward achieving these objectives.