Senior Data Scientist (I & II)

Overview

This is a general posting for multiple Senior Data Science roles open across our 4-sided marketplace. Roles are open at both the L5 (Senior Data Scientist I) and L6 (Senior Data Scientist II) levels. You’ll get the chance to learn about the different problems the Data Science team solves as you go through the process. Towards the end of your process, we’ll do a team-matching exercise to determine which of the open roles/teams you’ll join. At the bottom of this posting, you’ll find a breakdown of the currently open roles.

About the Job

• Own analytical frameworks that guide the product roadmap.
• Design rigorous experiments and interpret results to draw detailed and actionable conclusions.
• Develop statistical models to extract trends, measure results, and predict future performance of our products.
• Build simulations to project the impact of various product and policy interventions.
• Enable objective decision-making across the company by democratizing data through dashboards and other analytical tools.
• Use expertise in causal inference, machine learning, complex systems modeling, behavioral decision theory, etc., to shape the future of Instacart.
• Present findings in a compelling way to influence Instacart’s leadership.

About You

Minimum Qualifications

• 5+ years of experience working in a quantitative role at a product company or a research organization.
• Ability to run rigorous experiments and generate scientifically sound recommendations.
• Ability to write complex, efficient, and eloquent SQL queries to extract data.
• Ability to write efficient and eloquent code in Python or R.
• A desire to build and improve consumer software products.
• Ability to translate business needs into analytical frameworks.
• Eagerness to learn, flexibility to pivot when needed, savviness to navigate a dynamic environment, and a growth mindset to build a successful team and company.

Preferred Qualifications

• Awareness of business trade-offs when working on a multi-sided marketplace.
• Confidence in collaborating with and influencing cross-functional stakeholders (e.g., Product, Engineering) at a senior level.
• MS/PhD in Statistics, Economics, Applied Mathematics, or a related field.

Currently Opened Roles

Order Experiences (Search) | Sr. Data Scientist I (L5/6)

The Order Experiences (Search) team is focused on making it fast and effortless for customers to find the right items and complete their order with confidence. As a Senior Data Scientist, you’ll own the analytics and experimentation strategy that powers how we interpret customer intent and surface the most relevant results—driving search conversion, order rate, and GTV. You’ll partner closely with Product, Engineering, and ML to shape the roadmap for search relevance and ranking quality, running experiments across retrieval, ranking, and search UX while connecting offline model evaluation to real-world business outcomes.

Delivery | Sr. Data Scientist II (L6)

The Delivery team is dedicated to ensuring customers receive their complete orders seamlessly, spanning the full flow from capturing customer information to coordinating the shopper experience. As a Senior Data Scientist II, you’ll identify strategic opportunities to enhance the delivery experience, design and execute rigorous experiments to evaluate new product features, and leverage geospatial data and advanced analytical techniques to optimize logistics. You’ll also proactively identify high-risk delivery scenarios and develop solutions to the underlying systemic issues that drive them.

Marketing | Sr. Data Scientist I (L5)

The Marketing Data Science team is responsible for measurement and optimization across Instacart’s paid digital channels, including search, shopping, display, social, and video. As a Senior Data Scientist, you’ll build and maintain sophisticated attribution models—including multi-touch and incrementality-based approaches—and develop scalable data pipelines to turn raw marketing data into clean, analysis-ready datasets. You’ll apply causal inference methods such as geo holdouts and difference-in-differences to evaluate campaign effectiveness, partnering closely with marketing, data engineering, and business teams to define measurement frameworks and drive data-informed decisions. You'll also model user lifetime value (LTV) across acquisition cohorts, quantifying how marketing spend and channel mix influence long-term retention and monetization to inform budget allocation and growth strategy

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