Data Science PhD Intern

Job Description

Data Science PhD Intern

Instacart

Remote

Posted 14 hours ago

Overview

Job description

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