Senior Data Scientist I - Meals

Remote · 4+ years experience · Full-time · Remote · Posted Sep 28, 2026

At a glance

We are looking for a Senior Data Scientist to lead the Meals initiative, which is one of Instacart's top strategic priorities for 2027.
This role focuses 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 to 1 initiative.

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 to 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 including 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

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

Flex First team offering flexibility to choose where to work from home, an office, or other locations