About the role
ML Research Scientist - Guac
At Guac, we're solving grocery food waste with predictive ML. We predict exactly how much of each product will sell, helping grocery retailers order/produce the perfect amount of inventory.
The grocery industry is enormous (in the US, it accounts for 4% of GDP), and grocery food waste is one of the biggest drivers of cost for retailers, but also a huge problem for the climate and food security.
Today, we're working with major supermarket chains in the US (you've probably shopped at some of them before), and we've scaled to 7-figures in ARR. We're also backed by leading investors such as Y Combinator, 1984 Ventures, Collaborative Fund, and angels from Instacart and Citadel Securities.
We've brought together an exceptional team from Palantir, BCG, Oxford, Cambridge, and MIT to solve intellectually challenging problems and tackle food insecurity & waste with technology.
We're looking for a talented ML Research Scientist in NYC to join our mission.
About the Role
As an ML Research Scientist at Guac, you'll be at the forefront of developing cutting-edge machine learning models that power our demand forecasting and inventory optimization systems. You'll tackle complex, multi-dimensional problems involving perishable goods, supply chain dynamics, and retail operations at unprecedented scale.
Your work will directly impact millions of dollars in inventory decisions across major grocery chains, helping reduce food waste while ensuring customers have access to fresh products. This is a highly experimental role where intellectual curiosity and methodological rigor will drive measurable business outcomes.
Core Responsibilities:
- Advanced Forecasting Models: Design and implement state-of-the-art ML models for demand forecasting at store, chain, and warehouse levels, accounting for seasonality, promotions, weather, and complex interaction effects
