
Python
Experienced
Data Engineer
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4+ years
Data Engineering
B.Sc. Bachelors Degree in Mechanical Engineering
Masters Degree in Data Science
Data Engineer with extensive experience in data modeling using machine learning, business intelligence, and managing the overall data flow, data processing and modeling process. Proven ability to develop business solutions by analyzing and interpreting data to create value. Always eager to learn new bleeding edge technologies.
I had the honor of building the Data Science team at the company where I was consulting while working for Horbath Technologies. During this time, I led multiple projects, including deploying over 200 machine learning models for natural gas consumption prediction.
Currently, I am consulting for Pacific Salmon Company as part of my Masters capstone project, where I have developed several interpretable models orchestrated using an Apache Airflow pipeline. This work has helped the biologists on the team better allocate resources and provided cleaner data for the data team, enhancing overall project efficiency.
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This project showcases the complete pipeline of consuming, processing, and modeling data in Snowflake using the Medallion Architecture (Bronze, Silver, Gold). All transformation logic is implemented through Snowflake Stored Procedures written in JavaScript, demonstrating how to keep processing close to the data for performance and maintainability.
Autopredictor simplifies machine learning model selection for regression tasks. This Python package provides an intuitive approach, minimizing coding for model exploration.
Using pretrained Transformers, and Recurrent Neural Networks, this project uses scraped lyrics and musical data to generate music and lyrics.
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