How Instacart is Using Deep Learning to Create the Most Efficient Shoppers Ever

Instacart has revolutionized grocery shopping by bringing groceries to your door in a little as an hour. The crux of the company is their shoppers, who shop in brick and mortar stores and bring the food to customers thousands of times per hour. Making these shoppers as efficient as possible is critical to the business. Hear how Instacart is applying deep learning to the shopping list to improve shopper efficiency, predicting the sequence that shoppers pick items in specific store locations - in some cases saving significant time in-store. Jeremy will discuss the data collection, mobile technology and machine learning approaches Instacart is applying to enable on-demand grocery delivery.

Jeremy Stanley, VP of Data Science at Instacart

Jeremy is currently the VP of data science at Instacart, conquering the world one carrot at a time. Jeremy leads a team of data scientists who are integrated into product teams to drive growth and profitability through logistics, catalog, search, consumer, shopper, and partner applications. Previously, Jeremy was chief data scientist and EVP of engineering at Sailthru, CTO of Collective, and founded and led the Global Markets Analytics Group at Ernst & Young (EY), which analyzed the firm’s markets, financial and personnel data to inform executive decision making. Jeremy holds an MBA from Columbia.

Cookies help us deliver our services. By using our services, you agree to our use of cookies. Learn more