Job 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. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview We are looking for a Senior Data Scientist to lead the Meals initiative — one of Instacart's top strategic priorities for 2027. This role is focused on scaling data science work following the MVP launch, with metric tracking and experimentation at the core. You will play a key role in driving engagement, activations, and reactivations for Instacart through a high-visibility, high-impact 0→1 initiative. This is an opportunity to shape the direction of a major product area in close partnership with Product, Engineering, and Design. About the Job Lead data science for the Meals initiative, owning the post-MVP scale-up of DS systems and infrastructure Design, build, and maintain metric tracking frameworks to measure the impact of Meals on engagement, activation, and reactivation Drive experimentation strategy — from hypothesis definition to analysis and recommendation — to guide product decisions Partner closely with Product Managers, Engineers, and Designers to align on strategy and communicate data-driven insights Contribute to a 0→1 initiative at a critical inflection point, helping define what success looks like at scale About You Minimum Qualifications Proven experience in consumer-facing product data science, partnering closely with Product Managers, Engineering Leads, and Data Engineers Strong data science foundation: product and data analysis, A/B experimentation, causal inference, and statistical modeling Experience defining KPIs, and optimizing funnel for product market fit Excellent communication skills, with the ability to synthesize complex technical findings for senior business and engineering stakeholders 4+ years of work experience in a data science or related field Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Economics, Engineering) or equivalent practical experience Preferred Qualifications Experience bridging offline evaluation metrics (e.g., NDCG, precision/recall, human evaluation) with online experiments and business outcomes. Background in causal inference beyond standard A/B tests (e.g., holdouts, diff-in-diff, quasi-experiments) to measure long-term or cross-surface effects. Proven impact improving logging, instrumentation, and metric definitions in complex data environments. Experience launching new features in new markets, or launching 0-1 initiatives #LI-Remote Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here . Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please rea d more about our benefits offerings here . For US based candidates, the base pay ranges for a successful candidate are listed below. CA, NY, CT, NJ $194,000 — $204,500 USD WA $185,000 — $195,500 USD OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI $177,000 — $187,000 USD All other states $161,000 — $170,000 USD

Requirements

Must-haves

We're transforming the grocery industry
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
Lead data science for the Meals initiative, owning the post-MVP scale-up of DS systems and infrastructure
Design, build, and maintain metric tracking frameworks to measure the impact of Meals on engagement, activation, and reactivation
Drive experimentation strategy — from hypothesis definition to analysis and recommendation — to guide product decisions
Partner closely with Product Managers, Engineers, and Designers to align on strategy and communicate data-driven insights
Contribute to a 0→1 initiative at a critical inflection point, helping define what success looks like at scale
Proven experience in consumer-facing product data science, partnering closely with Product Managers, Engineering Leads, and Data Engineers
Strong data science foundation: product and data analysis, A/B experimentation, causal inference, and statistical modeling
Experience defining KPIs, and optimizing funnel for product market fit
Excellent communication skills, with the ability to synthesize complex technical findings for senior business and engineering stakeholders
4+ years of work experience in a data science or related field
Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Economics, Engineering) or equivalent practical experience

Nice-to-haves

Experience bridging offline evaluation metrics (e.g., NDCG, precision/recall, human evaluation) with online experiments and business outcomes.
Background in causal inference beyond standard A/B tests (e.g., holdouts, diff-in-diff, quasi-experiments) to measure long-term or cross-surface effects.
Proven impact improving logging, instrumentation, and metric definitions in complex data environments.
Experience launching new features in new markets, or launching 0-1 initiatives

Application prep

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