SHORT INTRO	AI/ML Engineer and Data Analytics specialist building end-to-end pipelines, explainable ML systems, and decision-grade reporting layers across NLP, LLM, compliance, and customer intelligence workflows.
🔭 CURRENTLY WORKING ON	Building production-grade agentic AI systems and revenue intelligence architectures that connect Python, SQL, Power BI, and explainable ML into one decision pipeline.
👯 LOOKING TO COLLABORATE ON	Advanced ML architecture, NLP products, explainable prediction systems, and analytics platforms where models, dashboards, and business action need to work together.
🤝 LOOKING FOR HELP WITH	Scaling hardware-native local inference, robust MCP orchestration, and enterprise-grade semantic reporting models that bridge Python pipelines with Power BI and DAX.
🌱 CURRENTLY LEARNING	Deepening protocol-driven AI engineering, production model serving, and advanced metric architecture for explainable ML and dashboard-first decision systems.
💬 ASK ME ABOUT	Power BI, DAX, XGBoost, SHAP, NLP, LLM research, MCP-based agentic systems, SQL pipelines, and analytics storytelling for stakeholder decisions.
⚡ FUN FACT	I like systems where the model and the dashboard agree — from turning failing compliance signals into 100% audit scores to making churn predictions useful before revenue disappears.

Recovered a high-value client account by converting four months of declining performance into sustained 100% compliance outcomes.

Architected SQL and Python automation layers that compressed manual reporting cycles into a live operational reporting system.

Built a churn and LTV intelligence engine with SHAP-driven explainability to surface actionable risk signals for business teams.