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.

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

Understanding customer buying patterns and retention behavior.

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

Predictive Revenue Engine & Shark Detector | Recovering Unattributed Luxury Segment Income via Algorithmic Lead Scoring (Random Forest) and LTV Regression. Built with BigQuery, Parquet, and Streamlit.

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.

Fintech Optimization Engine: Achieving 32% Conversion Lift & 5.6% Revenue Growth via Rigorous A/B Testing. Features Power Analysis (80% Standard), Live Market API Ingestion, and Automated Executive Decision Logic.

An independent capstone project in Business Data Management focusing on Revenue Optimization for a Freight Forwarding MNC in India conducted over 6 months.

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.

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

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.

B2B sales pipeline audit platform — find revenue leakage across 5 pipeline stages. Built for Pakistan, UAE & Saudi markets. Free audit tool + 120-industry benchmark calculator.

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

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

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

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.

End-to-end customer churn prediction system using machine learning, feature engineering, and probability calibration. The project goes beyond prediction by optimizing decision thresholds based on business profit, implementing customer segmentation, lift analysis, and explainable AI (SHAP) to support data-driven retention strategies.