I build real-time data pipelines and turn raw data into decisions that matter. Currently completing my Master's in Data Analytics & Information Systems at Texas State University, Graduate Merit Fellow. Actively seeking full-time roles in data engineering and analytics, available with OPT upon graduation.
Capabilities
End-to-end skills across data engineering, analytics, and cloud. Built through hands-on projects, not just coursework.
Python (Pandas, NumPy, Scikit-learn), R, SQL (Advanced), ETL Workflows
Tableau, Power BI, Looker, Matplotlib, Seaborn, Excel
AWS EC2, S3, Glue, Athena, Apache Kafka, Snowflake, Databricks
Random Forest, K-means Clustering, Predictive Modeling, Feature Engineering
MySQL, MongoDB, Snowflake, Data Validation, NoSQL, Relational Databases
Linear & Nonlinear Programming, Operations Research, Vehicle Routing, Max Flow
Portfolio
These aren't classroom exercises. Each project was scoped, built, and shipped independently. The same work you'd expect from a junior data engineer or analyst on your team.
Designed and deployed a production-grade streaming pipeline that ingests live stock market data at 1 message/second via a Python Kafka producer. Data lands in an S3 data lake as JSON, with AWS Glue auto-detecting schema changes and Amazon Athena enabling real-time SQL analytics on top. Built end-to-end on EC2, covering the full stack a data engineer would own at a fintech or trading firm.
View ProjectAnalyzed 3M+ grocery orders to surface patterns in customer purchasing behavior, including peak ordering windows, top reorder categories, and basket composition trends. The kind of analysis a retail data analyst would deliver to a merchandising or marketing team to drive inventory and promotional decisions.
View AnalysisBuilt a full ETL pipeline across 9,994 retail orders: extracted and cleaned raw transactional data with Pandas, loaded into MySQL, and queried with advanced SQL: window functions, CTEs, and month-over-month growth analysis. Delivered structured reporting on sales trends from raw data to insight, end-to-end.
View ProjectBuilt a supervised ML model predicting student academic outcomes with 89% accuracy using a Random Forest classifier trained on demographic and behavioral features. Applied the full ML workflow: feature engineering, cross-validation, and hyperparameter tuning, in a domain where early prediction directly supports student intervention and success.
View NotebookEnd-to-end stock price forecasting app using Meta's Prophet time-series model. Fetches historical price data from Tiingo, trains a model on 5 years of daily closes, and returns a 7–90 day forecast with confidence intervals. Built a FastAPI backend and a Streamlit frontend so anyone can use it in a browser — no code required. Deployed on Render.
Live DemoGet In Touch
I'm actively looking for full-time roles in data engineering or analytics, available with OPT upon graduation. Whether you have an open role or just want to connect, I'd love to hear from you.