Spectral
Zane Peycke began their work experience as a Machine Learning Engineer at Spectral in 2021. Prior to that, from 2020 to 2021, they worked as a Research Assistant at Columbia University in the City of New York. In this role, they conducted machine learning research, developed manipulated media detection applications, and created remote meeting accessibility tools.
In 2020, Zane worked as a Data Analyst at GRID3. Here, they analyzed spatial data, assessed data quality for various locations, and created Python scripts to clean and merge large volumes of data.
From 2017 to 2019, Zane served as a Research Assistant at the University of Washington. Their research focused on two-dimensional material nanophotonic systems. Zane also worked as a Digital Systems and Information Technology Student Assistant, responsible for computing resources at the University of Washington Libraries. Additionally, they had another research assistant role in 2018.
Zane Peycke completed their Bachelor of Science degree in Physics with a Minor in Art History at the University of Washington from 2016 to 2019. Following this, they pursued a Master of Science degree in Data Science at Columbia University from 2019 to 2021.
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Spectral
Spectral is a protocol for programmable creditworthiness. The company partners gain valuable credit risk insights to optimize business decisions and offerings by leveraging on-chain data; users gain access to new financial opportunities. The Multi-Asset Credit Risk Oracle (MACRO) Score is an on-chain equivalent to a traditional FICO score thatallows users to check their on-chain scores through its platform.Spectral was founded in 2020 and is based in New Rochelle, New York.