My name is Siavash
(pronounced Si: ɑ: 'væʃ)
Senior Data Scientist at Fanatics Collectibles
I'm a Python enthusiast who crafts intricate machine learning models with unwavering passion, transforming data into captivating narratives and elegant visualizations. As a dedicated data scientist, machine learning engineer, and seasoned programmer, I thrive on developing innovative tools and solutions to address the latest challenges faced by business stakeholders. My professional journey has predominantly revolved around constructing machine learning models, designing data pipelines, creating automation software, conducting experiments, simulations, and masterfully weaving narratives through data.
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Throughout my tenure at Zest AI, I dedicated my efforts to meticulously crafting robust data pipelines and innovative machine learning solutions. Our primary goal was to empower small banks and credit unions with state-of-the-art, equitable, and transparent credit underwriting systems. By leveraging these advanced systems, we enabled these financial institutions to make informed and fair decisions, ultimately enhancing their ability to better serve a diverse clientele.
In a previous chapter of my career, I delved into the cosmos as a computational cosmologist at the University of Southern California. My research was centered on modeling, simulating, and analyzing cosmological data, with a specific emphasis on the intricate details of the Cosmic Microwave Background (CMB). I delved into the statistical measurement of large-scale velocity fields and explored the nuanced implications of relativistic Doppler and aberration effects on CMB observations. Notably, my post-doctoral research contributed significantly as a member of the Simons Observatory and the CMB-S4 collaborations.
More about me: I love coding, point & click games, and whodunit novels.