Senior Data Scientist (Meals)

Instacart

New-York, United States Posted October 2, 2026

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Remote Full-time Senior
Salary Range

$161,000 - $204,500

Job Description

Join our team as a Senior Data Scientist for the Meals initiative. In this role, you will lead data science efforts, design and maintain metric tracking frameworks, drive experimentation strategy, and collaborate closely with Product Managers, Engineers, and Designers. You will contribute to a critical 0→1 initiative and help define success at scale. The ideal candidate will have a strong data science foundation, experience in consumer-facing product data science, and a background in causal inference.

  • Lead data science efforts for the Meals initiative, focusing on the post-MVP scale-up of data science 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.
  • Excellent communication skills, with the ability to synthesize complex technical findings for senior business and engineering stakeholders
  • Proven experience in consumer-facing product data science, partnering closely with Product Managers, Engineering Leads, and Data Engineers
  • Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Economics, Engineering) or equivalent practical experience
  • 4+ years of work experience in a data science or related field
  • 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
  • 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
  • Experience bridging offline evaluation metrics (e.g., NDCG, precision/recall, human evaluation) with online experiments and business outcomes
  • Proven impact improving logging, instrumentation, and metric definitions in complex data environments
  • Experience launching new features in new markets, or launching 0-1 initiatives
Required Skills
data science A/B testing collaboration communication statistics data analysis KPIs
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