Data Science PhD Intern

Instacart
4h$31 - $41Remote

About The Position

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. 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

Requirements

  • 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.

Nice To Haves

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

Responsibilities

  • 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.
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