[Remote] Ads AI Analytics Lead II

Note: The job is a remote job and is open to candidates in USA. Instacart is transforming the grocery industry by providing essential services for grocery delivery. As the Ads AI Analytics Lead, you will own the intelligence behind Ads agents, designing systems that improve campaign performance and collaborating with cross-functional teams to drive revenue growth and operational efficiency.

Responsibilities

• Define Ads ontologies and canonical metrics across campaigns, budgets, bids, creatives, audiences, and placements to power consistent reasoning and recommendations
• Build robust dbt models and curated marts in Snowflake (or BigQuery) with clear data contracts, tests, SLOs, and monitoring; orchestrate pipelines with Airflow
• Ingest, structure, and enrich unstructured Ads content; publish retrieval-ready datasets leveraging managed search/vector services to enable high-quality grounding
• Design and evaluate RAG workflows (hybrid search, re-ranking) with explicit quality and latency targets; iterate via offline/online experiments to improve performance
• Design agent reasoning, tools, and policies for Ads use cases, including human-in-the-loop approvals and guardrails that balance safety, cost, and speed
• Establish evaluation suites and dashboards tracking precision/recall, calibration, hallucination rate, latency, and cost; drive continuous model and system improvements
• Run A/B and uplift experiments to quantify business impact; own KPIs such as ROAS lift, pacing accuracy, RCA precision/recall, forecast MAPE, and time-to-insight
• Partner with Ads Product, Ads Engineering, Sales leadership, Data Engineering, and R&D to align roadmaps, de-risk launches, and ship high-quality production agents
• Own your workstream end to end—from data and pipelines to the UI and agent logic—delivering secure, observable, and reliable tooling that’s adopted by the field

Skills

• 4–7 years of experience in analytics engineering, data science, or applied AI, with advanced proficiency in Python and SQL
• 2+ years working with ads, retail, or e‑commerce data
• Hands-on experience with dbt and Snowflake or BigQuery, including data modeling, testing, documentation, and managing data contracts
• Experience orchestrating data pipelines with Airflow (or a similar scheduler), including alerting and on-call support for data SLOs
• Ability to design and run offline/online evaluations and A/B or uplift tests; familiarity with experiment design and statistical inference
• Fluency in Ads analytics concepts: ROAS, CPA, CTR, CVR, LTV, pacing, auction dynamics, and incrementality
• Shipped at least one production data or AI system used by business stakeholders, with demonstrable business impact
• Experience with evaluation and guardrail frameworks and human‑in‑the‑loop QA workflows
• Proficiency with at least one BI/visualization tool (e.g., Looker, Tableau, Mode, or Power BI)
• Bachelor's degree in a quantitative field (e.g., Computer Science, Engineering, Statistics) or equivalent practical experience
• Experience building AI-driven products or agents end to end, including retrieval design (hybrid search, re-ranking) and vector search
• Deep expertise in advertising products and operations, with a track record of driving automation that improved ROAS, pacing, or operational efficiency
• Applied experience with Ads modeling techniques such as forecasting, anomaly detection, uplift modeling, and causal inference
• Hands-on experience with workflow automation or internal tooling (e.g., Retool, Superblocks, Zapier, n8n, Gumloop) and/or front-end frameworks (e.g., React) to translate insights into actions
• Familiarity with retail media and ad ecosystems (e.g., Amazon Ads, Google Ads, Meta, Shopify, DoorDash) and their measurement frameworks

Benefits

• Instacart provides highly market-competitive compensation and benefits in each location where our employees work.
• This role is eligible for a new hire equity grant as well as annual refresh grants.

Company Overview

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