Welcome to episode 220 of the AI in Action podcast, the show where we break down the hype and explore the impact that Data Science, Machine Learning and Artificial Intelligence are making on our everyday lives.

Powered by Alldus International, our goal is to share with you the insights of technologists and data science enthusiasts to showcase the excellent work that is being done within AI in the United States and Europe.

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

Why she loves working at Shelf Engine

To find out more about Shawn and all the great work happening at Shelf Engine, check out the website www.shelfengine.com or follow them on Twitter @ShelfEngine. You can also follow her on Twitter @slramirez646 or connect with Shawn on Linkedin.

What did you think of Shawn’s podcast? Where do you see the future of AI and Data Science heading in the next few years? We would love to hear your thoughts on this episode, so please leave a comment below.

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