Comprehensive marketing analytics and measurement strategies covering modern data analysis, attribution modeling, and ROI optimization methodologies. Turn data into actionable marketing insights.

NexusFlow: Autonomous Ad-Quant Engine. High-performance infrastucture for TikTok & Google Ads. Features: Rebalanced Risk Engine, Real-time Attribution & Budget Egzecutor. Optimized with Python, Redis Cache & SQL. Forecasts spend with precision, managed via YAML & Slack. Propietary. Contact for private repo access.

Master repository containing the complete marketing philosophy, strategy, and comprehensive framework. The central hub that ties together all specialized marketing areas into a cohesive, integrated approach for modern marketers.

An end-to-end data analytics platform analyzing nano-influencer performance across 40+ markets. Built with Python and Streamlit, it features automated ETL pipelines, sentiment-weighted engagement tracking, and strategic budget-allocation modeling

Causal inference project using DoWhy to isolate the true marketing lift of bank contact methods. Applies Propensity Score Stratification to remove selection bias from raw campaign data and delivers an interactive ROI simulator for budget decision-making.

Mathematical optimization tool using Gurobi/MIP to maximize ROI for a $10M multi-channel marketing budget under complex strategic and business constraints.

Optimized Air France's online advertising campaigns using advanced regression modeling and data analysis, uncovering actionable insights to maximize ROI and enhance ad performance.

🚀 AI-powered marketing automation with 75% time reduction & 23% ROI improvement. MCP server for Claude integration.

Statistical analysis comparing Facebook vs AdWords ad campaign performance using A/B testing, hypothesis testing, and regression analysis to optimize marketing ROI

Reproducible Marketing Mix Modeling (MMM) pipeline with adstock optimization and ROI-based budget allocation simulation using Python.

Financial ROI analysis of MBG.DE stock (2020-2022) using Python and AI-optimized code

ML-powered customer retention solution for banks undergoing digital transformation, optimizing a limited budget with targeted strategies based on churn prediction and digital readiness segmentation.

Predicting customer churn with a focus on financial impact. Optimized machine learning models using cost-benefit analysis to maximize ROI rather than just accuracy.