operations-analytics

UNS-native, cybersecurity-aware multi-agent reference architecture for U.S. small-to-mid manufacturers. Industrial agentic intelligence aligned with ISA-95, NIST AI RMF, and CMMC L2.

End-to-end café inventory project: clean transaction data, build daily item-level demand series, backtest strong baseline forecasters, generate next-30-day demand forecasts, convert forecasts into safety stock + reorder points, and validate policies with Monte Carlo stockout-risk simulations, wrapped in a Streamlit dashboard.

End-to-end E-Commerce Delivery Operations Intelligence platform with analytics, demand forecasting, capacity planning, operational risk insights, Streamlit dashboard, Docker, CI/CD, and cloud deployment.

AI-powered operations monitoring system that detects issues, scores severity, chains root causes, and delivers automated PDF reports via email — built with Python, Claude API, and ReportLab

Multi-agent AI system for logistics, finance, and growth marketing intelligence using FastAPI, LLM orchestration, memory, and real-time streaming.

End-to-end Business Intelligence & Data Engineering project analyzing food delivery logistics, financial performance, and customer cohorts.

A Python-based decision support tool that forecasts short-horizon demand, evaluates capacity utilization risk, and produces prioritized mitigation actions with backtest accuracy (MAE/MAPE) and a professional PDF report.

Operational analytics pipeline that detects workflow inefficiencies in ITSM ticket lifecycles and simulates cost-saving interventions.

SQL-based analytics pipeline for identifying revenue leakage in CPG supply chains using DuckDB, Python, and synthetic trade spend data

The project provides insights and recommendations to improve the operations of a fictional pizza restaurant by analyzing daily and hourly order volume, utilization of seating capacity, performance of menu items, and inventory of over 48,000 rows of transaction data through data modeling and visualization in Power BI.

Operational supply chain analytics project using SQL and Python to analyze demand trends, procurement activity, delivery performance, inventory classification, and operational KPIs.

Audit disparities in operational ML systems

Synthetic multi-branch operations analytics portfolio demonstrating KPI design, SQL, Python, Power BI modeling, data quality, and business requirements.

End-to-end healthcare claims analytics: Synthea → DuckDB → dbt (sources/staging/intermediate/marts) → Streamlit + Plotly ops UI. Surfaces $2.6M outstanding across 14K claims with a ranked priority queue, claim-level drill-down, and explainable "why flagged" rules. Modern data stack portfolio build.

Simulated operations case study comparing 4x10 vs 6x6-7 workforce allocation for throughput stability, backlog control, and labor-cost efficiency.

Energy services analytics pipeline using Python, SQL, Airflow, and Tableau.

Data analytics project simulating industrial cleaning operations with PostgreSQL, Streamlit and geospatial insights.

End-to-end downtime analytics pipeline using Python, SQL, and ETL to compute reliability KPIs (MTBF/MTTR) and failure-mode insights for operational systems.

An Excel, Python and SQL inventory model that identifies what to order and which excess stock needs review.