Data Scientist & Data Engineer • AWS • Python • ML • Big Data
I’m a Data Analyst / Data Engineer with an MS in MIS (SDSU 
). I’ve worked at the intersection of embedded systems and data—building ETL pipelines, big‑data integrations, and ML for predictive maintenance and anomaly detection. Comfortable across Python, SQL, AWS, Snowflake, Kafka, Spark, Airflow, Tableau, and R, I turn raw controller and sensor data into reliable, decision‑ready insights. I collaborate closely with hardware and project teams to improve product reliability, efficiency, and data quality.
A lightweight local agent running with Ollama + Llama 3.1. Adds a reasoning loop, tool calls (calculator, web_search), and simple RAG on your own files.
A collection of small ML/Analytics/SQL projects demonstrating techniques across preprocessing, modeling, and visualization.
This site: custom animated UI + AOS, particles, dark/light mode, client‑side AI chatbot, and optional Jekyll pages.
Fowler College of Business, SDSU — Research Assistant · Aug 2024 – Present
Analyzed foot‑traffic and business outcomes (regression, time‑series); built supervised models and KMeans clustering for regional mental‑health trends; created dashboards with Matplotlib/Seaborn/Tableau; ran literature reviews and statistical tests (chi‑square, ANOVA); supported survey design and data collection.
Frontline operations and customer support while studying; strengthened communication and problem‑solving.
Primary point of contact for student residents; troubleshooting and service coordination.
Built end‑to‑end ETL for sensor logs and PI/SCADA data using Python, SQL, Snowflake, Kafka, and AWS (S3, EC2); deployed ML‑ready models and real‑time Tableau dashboards for efficiency & fault trends; scaled distributed processing on Spark and Airflow; improved DAG design & scheduling, boosting pipeline efficiency by ~25%.
Automated Python QA for embedded controllers (‑17% manual effort); audited test‑log data with SQL; improved logging protocols, increasing downstream analytics reliability (~22%).
Hands‑on SQL analysis and database tasks (retrieval, manipulation, optimization).