Senior Manager, Marketing Decision Science

Overview

The Marketing Data Science & Analytics (MDSA) team is Instacart's analytical engine for Paid Media, SEO, and Retailer Marketing — partnering with channel leaders, Finance, and senior marketing leadership to ensure every investment dollar is guided by rigorous, causal measurement. The team owns paid channel analytics, incrementality testing, goal-setting and pacing, LTV-based optimization, and a marketing measurement roadmap anchored on Media Mix Modeling, Experiments, LTV & Touchpoints — Instacart's evolving single source of truth for marketing impact. We're looking for a Senior Manager to lead the Marketing Decision Science team — a group of Decision Scientists embedded across Paid Media, SEO, and Retailer Marketing. This is a high-visibility role with direct exposure to marketing leadership and regular presence in senior forums including MBRs, SBRs, and Pacing Meetings. This role reports to the Director of Marketing Data Science & Analytics.

Responsibilities

• Lead and develop a team of 5 Decision Scientists and Marketing Analysts, owning their performance, growth, and day-to-day direction — setting and enforcing a high quality bar across all team output
• Own the end-to-end delivery of MDSA's paid marketing analytics workstreams: channel-level goal-setting, pacing, incrementality testing, acquisition and retention analysis, and Retailer Marketing measurement
• Lead the team's contribution to the unified marketing measurement framework - MMM, incrementality testing, LTV, MTA — coordinating MMM inputs, incrementality test organization, and reporting
• Drive re-goaling, rebasing, and scenario modeling exercises that directly inform how Instacart allocates its marketing budget
• Serve as the primary analytical point of contact for senior marketing leadership and Finance — owning those relationships independently and representing MDSA in MBRs, SBRs, and Pacing Meetings
• Define and drive the Marketing Decision Science roadmap in partnership with the Director, translating business priorities into sequenced analytical investments
• Partner with Marketing Data Science on Measurement architecture, LTV modeling, and measurement infrastructure
• Identify opportunities to improve analytical self-serve and reduce recurring reporting burden through tooling and