I build production-style AI systems, including LLM applications, RAG pipelines, and end-to-end ML workflows.
My work focuses on combining LLMs, machine learning, and data engineering into real-world, production-ready applications.
My work spans:
- LLM applications (RAG pipelines, tool-augmented agents, conversational memory)
- Machine learning (PyTorch, Scikit-learn)
- ML engineering (FastAPI, MLflow, Docker)
- Data systems (PySpark, DuckDB, cloud pipelines)
Production-style AI assistant demonstrating LLM orchestration, retrieval pipelines, and tool-augmented reasoning.
Built with Streamlit featuring:
- Retrieval-Augmented Generation (RAG)
- Tool execution (calculator via AST parsing)
- Conversational memory
- Modular architecture
Tech: Python, Streamlit, LLMs
💼 Use Case: AI assistant capable of answering questions from documents, performing calculations, and maintaining conversational context.
🧱 Architecture: Modular pipeline with retrieval layer, tool execution layer, and memory management
Machine learning–based recommendation system for dog breed selection, deployed as an interactive Streamlit application.
Production-style ML system covering the full lifecycle:
- Model training
- Experiment tracking (MLflow)
- API deployment (FastAPI)
Medallion architecture pipeline using DuckDB and modular ETL design.
🔍 Focus Areas: LLM applications, RAG systems, ML pipelines, and AI system design & architecture
A collection of analytics projects covering data cleaning, visualization, and business intelligence.
| # | Project | Description | Tools |
|---|---|---|---|
| 1 | Data Cleaning & Preparation | Retail Sales dashboard with AWS deployment — end-to-end data wrangling workflow with validation scripts. | Python · Pandas · AWS |
| 2 | Exploratory Data Analysis (EDA) | Customer Churn tracker deployed on Azure — statistical profiling and churn behavior analysis. | Python · Matplotlib · Azure |
| 3 | Excel Automation Dashboard | COVID-19 trend analysis with GCP integration — automated Excel reports powered by Python scripting. | Python · Excel · GCP |
| 4 | Power BI Retail Insights | Marketing Campaign ROI analytics — cross-channel marketing performance with Power BI dashboards. | Power BI · SQL |
| 5 | Tableau Global Sales Overview | E-commerce order automation using Python + Excel — visual storytelling with Tableau and automated ETL. | Tableau · Python |
| 6 | SQL Sales Optimization | Financial KPI tracking via SQL + Power BI — optimized queries for pricing and profitability insights. | SQL · Power BI |
| 7 | Predictive Modeling | Customer segmentation & RFM analysis with Tableau — machine-learning-based forecasting and insights. | Python · Tableau |
| 8 | Customer Segmentation | Supply Chain efficiency modeling with Power BI — advanced segmentation and dashboard optimization. | Power BI · SQL |
| 9 | A/B Testing & Statistical Analysis | Marketing campaign inference modeling — statistical testing to identify significant strategies. | Python · Statsmodels |
| 10 | Sales Forecasting | Time-series prediction using Python + Power BI — ARIMA and Prophet models for trend forecasting. | Python · Power BI |
| 11 | BI Data Modeling | Dimensional warehouse schema (SQL + Power BI) — data modeling and ETL processes for BI systems. | SQL · Power BI |
| 12 | Executive Insights Dashboard | Storytelling dashboard for business leaders — executive-level insights visualized in Power BI. | Power BI |
| 13 | Cloud Data Pipeline Capstone | End-to-end analytics pipeline on AWS + Power BI — full-stack ETL, storage, and BI pipeline. | Python · AWS · Power BI |
- 🌐 Website: darrellmortalla.com
- 💼 LinkedIn: linkedin.com/in/darrell-mortalla-77857012a
- 🐙 GitHub: github.com/dmortalla
“Data transforms decisions into measurable success.”
© 2025 Darrell Mortalla
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