Data-driven customer churn analytics, financial risk scenarios, and executive decision memo for leadership.
Comprehensive customer acquisition systems covering modern lead generation, conversion optimization, and customer onboarding methodologies. Build sustainable customer acquisition processes.
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.
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.
Real-time Steam pricing recommendations — combines Steam APIs, review sentiment and demand estimation to suggest revenue-optimal prices. Built at SpurHacks 2025.
AI-powered monetization decision engine for simulating pricing, revenue, customer impact, AI costs, and experimentation tradeoffs.
Applying product segmentation, demand forecasting, and revenue optimization to increase online retailer revenue
Understanding customer buying patterns and retention behavior.
Production-grade Causal AI engine that replaces flawed churn prediction with uplift meta-learners to target true Persuadables. Simulates enterprise SaaS revenue recovery, eliminates spend on Sure Things, and protects revenue from Sleeping Dogs.
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.
Dynamic pricing engine using XGBoost, price elasticity modeling, and A/B testing to optimize revenue, with a Streamlit dashboard.
A Reinforcement Learning agent built with Scikit-Learn and NumPy that optimizes product pricing strategies in competitive markets, achieving 28% revenue lift in simulations.
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.
Dynamic Pricing Optimization using Reinforcement Learning and Q-Learning to learn revenue-maximizing pricing strategies in a custom OpenAI Gym environment, featuring demand simulation and an interactive Streamlit dashboard.
Revenue management and pricing analytics - Price elasticity modeling, promotional ROI analysis, A/B testing for media industry
Enterprise Machine Learning & Knapsack Portfolio Optimization Engine achieving >40% NPV Lift under marketing budget constraints. Features interactive Streamlit dashboard, AI insights engine, REST API, and Docker.
🛒 Enterprise Dynamic Pricing Engine. A Big Data ML pipeline analyzing 1.2M transactions to predict demand elasticity and maximize gross margin with 94% accuracy.
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.
Post-ranking decision layer reordering recommendations by margin. +2.01% position-weighted yield with zero relevance loss, on 2.7M Retailrocket events.
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