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.

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

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.

End-to-end retail sales analysis using Excel | Revenue optimization insights | Interactive dashboards with actionable business intelligence

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.

A falta de traducción a inglés y piloto para Negocio

Анализ A/B-тестирования новой механики оплаты: оценка метрик, статистические тесты, рекомендации по внедрению и оптимизации.

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.

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

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

A Reinforcement Learning agent built with Scikit-Learn and NumPy that optimizes product pricing strategies in competitive markets, achieving 28% revenue lift in simulations.

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

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.