Senior Data Scientist - Ads Auctions

Job Description

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 The Ads Auctions team is responsible for innovating and enhancing auction mechanisms to create a competitive and transparent marketplace that benefits both advertisers and consumers. We focus on the full auction workflow—candidate filtering, pricing strategies, bid optimization, and selection processes—with the goal of balancing user experience with advertiser value. As a Senior Data Scientist on this team, you will be a core technical voice shaping how our auction systems evolve, driving improvements to our CPC (cost-per-click) infrastructure and bidding algorithms that directly impact advertiser performance and Instacart's ads revenue. About the Job Design and own analytical frameworks that guide the evolution of our auction and bidding systems, including CPC pricing, bid landscape modeling, and reserve price optimization. Run rigorous experiments to evaluate the impact of auction mechanism changes—such as bid shading, second-price vs. generalized second-price auctions, and dynamic pricing—and translate results into actionable recommendations. Develop statistical and machine learning models to forecast bid distributions, predict click-through rates, and optimize auction efficiency across advertiser and consumer dimensions. Build simulations to model auction dynamics and stress-test proposed mechanism changes before live deployment. Partner closely with Engineering, ML, and Prod

Required Skills