Data Science PhD Intern

OVERVIEW

At Instacart, data science is the compass that guides our product strategy. We operate a complex, four-sided marketplace involving customers, shoppers, retailers, and CPG partners. Our mission is to create a world where everyone has access to the food they love. To achieve this, we don't just analyze data; we use rigorous quantitative methods to understand causality, optimize market efficiency, and design the economic architecture of our platform.

We are looking for PhD students to join our Data Science & Analytics team for a 12-week summer internship. This role focuses on inference, experimentation, and strategy.

ABOUT THE JOB

You will be embedded within a specific product team where you will work closely with a senior member of the team to act as a strategic partner to Product and Engineering.

These are some of the potential teams you’d join:

• Ads
• Caper Smart Carts
• Consumer Growth and Marketing
• Ecosystem (informing high-level company strategy)
• Experimentation Platform
• Fraud & Payments
• Logistics, Marketplace & Fulfillment
• Shopper Experience & Engagement

Your impact:

• Ownership: You will work on and own a self-contained project that tackles an ambiguous business problem, using your research and analysis toolkit, to deliver actionable recommendations and/or applied prototypes.

• Solve ambiguous problems: You will take open-ended questions (e.g., "How does delivery speed affect long-term retention?" or "What is the optimal auction mechanism for new ad formats?") and structure them into solvable applied problems.
• Experimentation: Design and analyze complex experiments (e.g., switchback testing, difference-in-difference methods, quasi-experimental designs) to measure causal impact in a noisy multi-sided marketplace setting.
• Strategic deliverables: Go beyond analysis. You will synthesize your findings into strategic recommendations presented to senior leadership and cross-functional partners.

ABOUT YOU

We are looking for candidates who can bridge the gap between academic rigor and fast-paced industry application. This is an ideal opportunity to bring your strong domain expertise and apply in a real-world business context.

Minimum Qualifications:

• Currently enrolled in a PhD program in Computer Science, Economics, Statistics, Operations Research, or a related quantitative field. Note: We typically look for students within 6-12 months of graduation who are interested in exploring full-time industry roles in the future.
• Strong proficiency in SQL (ability to manipulate large datasets independently).
• Fluency in Python or R for statistical modeling and data analysis.
• Expertise in experimentation and applied statistical and machine learning methods (hypothesis testing, regression, causal inference, machine learning).
• Ability to "think on your feet," with a demonstrated ability to break down complex, unstructured problems.

Preferred Qualifications:

• Specialized research focus in Causal Inference, Econometrics, Experimental Design, Mechanism Design/Auctions, or Optimization.
• Prior internship experience or work with large-scale observational data.

THE INTERNSHIP EXPERIENCE

• Mentorship: You will be paired with a Senior Data Scientist mentor who will provide technical guidance, career coaching, and support throughout your 12 weeks.
• Real Impact: You will work on a specific, high-priority project.

DETAILS

• Timeline: 12 weeks (Summer 2026).
• Locations: Remote, although we have offices in the following cities, and so have a slight preference towards folks located in these places and want to spend time in-person:
• San Francisco, CA
• Toronto, ON
• New York, NY

#LI-remote