Today's guest is Shawn Ramirez, Head of Data Science at Shelf Engine in Seattle. Shawn is an accomplished data science leader and SME in causal inference, experimentation, Machine Learning, statistics, optimization and game theory. She drives AI product development building, testing, and leveraging statistical and cutting edge machine learning at scale on high impact problems. Shawn's passion is working on complex questions about behavior, users and customers.

Founded in 2015, Shelf Engine uses machine learning to help grocery stores dial in their orders to minimize waste and maximize profits.  Shawn joined the company in late 2020 and leads a high-performing team in data science, machine learning, research, ML Ops, causal inference and experimentation. Shawn and her team are working on forecasting and price optimization to solve the $160B food waste problem, lower prices and feed America.

In today's episode, Shawn tells us about:

Shelf Engine’s work within grocery forecasting,

Problems they are solving within food waste and hunger,

How they are applying Machine Learning to solve these problems,

What she looks for when hiring into the team,

Advice on how to become a leader within Data Science and

Why she loves working at Shelf Engine