Ads AI Analytics Lead Ii

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 The Commercial Scaled Intelligence (CSI) team is an AI-first team dedicated to delivering actionable commercial insights and scalable automation to drive revenue growth and operational efficiency across the company. The team focuses on intelligence generation, predictive analytics, and workflow automation to enable data-driven decision-making and optimize commercial performance. As an Ads AI Analytics Lead II, you will own the intelligence behind our Ads agents. You will design the Ads semantic/context layer and build vertical AI agents that analyze campaigns, diagnose performance, and recommend actions that improve ROAS, pacing, and partner outcomes. You will partner with Ads GTM, Product, Data Science, and Engineering to ship production agents with measurable lift.   About the Job Define Ads ontologies and metrics for campaigns, budgets, bids, creatives, audiences, and placements. Build dbt models and curated marts in Snowflake with clear data contracts, tests, and SLOs. Ingest and enrich unstructured Ads content and publish retrieval‑ready datasets using our managed search/vector services. Design and evaluate retrieval workflows (RAG) with existing services for hybrid search and re‑ranking; set quality/latency targets and iterate via experiments. Design agent reasoning and policies on ads, including tool definitions and human‑in‑the‑loop approvals. Establish evaluation suites covering precision/recall, calibration, hallucination rate, latency, and cost. Run A/B or uplift experiments to quantify impact and guide iteration. Translate Ads problems into agent behaviors and own KPIs such as ROAS lift, pacing accuracy, RCA precision/recall, forecast MAPE, and time‑to‑insight.   About You Minimum Qualifications 4–7 years in analytics engineering, data science, or applied AI with strong SQL and