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instacart
We’re transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community.
We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
OVERVIEW Instacart will increase the number of features launched by 2x by the end of 2026 by effectively using AI. A primary driver of knowing which features to launch includes analytical work traditionally performed by data scientists in collaboration with a product team. We are developing systems to accelerate analyses completed by data experts and enable anyone to self-serve most analytics questions.
You would be responsible for driving AI for Analytics data science work which includes: Product strategy: Using data to identify the most promising opportunity areas along with contributing data expertise to refine and develop new product ideas. AI expertise: You will be using and deploying a variety of AI systems in production settings.
Intelligent systems: Improving a product feature by adding intelligent functionality to the product that relies on data science methods including statistical and machine learning methods The role requires strong XFN collaboration where an ideal candidate can: Drive critical efforts to completion with little oversight, while occasionally jumping into roles adjacent to data science (i.e. data engineering, machine learning engineer, etc). Create the product roadmap Ruthlessly prioritize among requests from multiple competing stakeholders Act as a senior cross-functional leader of the team, aligning the team on principles, processes and goals
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