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.
Overview
The Fulfillment Data Science team works on problems at the core of Instacart's marketplace: how customers choose and experience delivery and pickup, and how we balance speed, reliability, and cost to deliver it. You'll join a collaborative team that works closely with frontier machine learning models, on a rich data set with fast feedback loops from design to production. You'll be a trusted partner to Product, Engineering, and Operations, turning complex marketplace questions into clear recommendations that shape the roadmap and reach leadership.
About the Job
- Use data science to shape how customers choose and experience delivery and pickup, from browsing through checkout and fulfillment
- Own the experimentation framework for all speed and service option tests, across both marketplace and enterprise
- Design and analyze experiments in a two-sided marketplace, adapting methods to fit the problem
- Measure tradeoffs between speed, reliability, cost, and customer experience, and turn them into product and strategy recommendations
- Connect operational changes to business outcomes such as growth, retention, and efficiency
- Work with Product, Engineering, and Operations to understand complicated systems and find the questions that matter most
- Build automation tools, metrics, and frameworks that help the broader team move faster
About You
Minimum Qualifications
- 5+ years of experience in a quantitative role at a product company or a research organization
- Track record of owning ambiguous, cross-functional problems end to end and influencing roadmap or leadership decisions
- Ability to design and run rigorous experiments and come up with scientifically sound recommendations
- Ability to write complex, efficient SQL queries and code in Python or R
- Ability to turn unstructured quantitative problems into business outcomes by translating business needs into analytical frameworks
- Eagerness to learn, flexibility to pivot when needed, and a growth mindset in a dynamic environment
Preferred Qualifications
- Experience with the analytical and strategic challenges of working on problems in a multi-sided marketplace
- Experience building, evaluating, and improving statistical, machine learning, and optimization models
- Experience working with geospatial data and methods
- Experience with experimentation in a product-driven setting and in developing experimentation capabilities and tooling
- Excellent written and verbal communication skills, able to lead initiatives across multiple product areas and communicate findings to leadership, product, and engineering teams
- MS/PhD in Statistics, Economics, Operations Research, Applied Mathematics, or a similar field
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