My name is Siavash
(pronounced Si: ɑ: 'væʃ)
Staff Data Scientist at Fanatics Collectibles
I’m a full-stack data scientist who bridges the gap between data and engineering. I work with complex datasets and turn them into clear insights and solutions that teams can act on. With a strong foundation in machine learning and software engineering, I focus on building reliable end-to-end data systems, writing production-ready code, and collaborating across disciplines to make data useful and impactful.
* * *
Professional Experience
Fanatics Collectibles – Staff Data Scientist
Los Angeles, CA | 2024 – Present
At Fanatics Collectibles, I lead machine learning and data platform initiatives that revolutionize athlete selection for our physical and digital products. By integrating diverse datasets—including performance metrics, social media trends, and market analytics—into a unified system, I have streamlined decision-making processes, significantly reduced research time, and enhanced product design scalability. Additionally, I am leading the development of a low-latency, multi-modal chatbot to educate and onboard new collectors, broadening our collector base through innovative AI-driven interactions.
Zest AI – Senior Data Scientist
Burbank, CA | 2020 – 2023
At Zest AI, I helped transform credit underwriting for small banks and credit unions by building and deploying end-to-end machine learning solutions. I led initiatives across data infrastructure, pipeline automation, and model development—enabling scalable, equitable, and explainable credit risk systems. I also built internal tools that accelerated the data science workflow across 100+ client projects and contributed to strategic experimentation that improved model accuracy and reduced risk for underserved populations.
University of Southern California – Research Scientist
Los Angeles, CA | 2015 – 2020
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.