About

Trace Levinson is an accomplished machine learning engineer and data scientist with over 5 years of experience in the field. With a background in quantitative economics, Trace has a unique perspective on the intersection of data science and business strategy. Currently, Trace is a Staff Machine Learning Engineer at Instacart, where they work on the fulfillment team. In this role, Trace applies their expertise in machine learning, optimization, and causal inference to optimize marketplace dynamics, helping Instacart deliver the best possible experience to its customers. Trace has a proven track record of success in the industry, having held senior positions at Instacart as both a Machine Learning Engineer and Data Scientist. Prior to joining Instacart, Trace worked on a variety of machine learning projects, including developing algorithms for predicting customer churn and building recommendation systems for e-commerce platforms. Trace's education includes an Advanced Machine Learning & Deep Learning Coursework from Coursera, as well as a Bachelor's Degree in Economics from the University of California, Berkeley, and a degree in Economics from Pontificia Universidad Católica de Chile. Trace's technical skills include expertise in machine learning, data science, and research science, with experience using a variety of tools and technologies. Overall, Trace is a highly skilled and experienced machine learning engineer and data scientist with a passion for using data to drive business success. With a strong background in economics and a deep understanding of machine learning and optimization techniques, Trace is an invaluable asset to any team looking to leverage data to gain a competitive advantage.