Ads AI Analyst

Instacart Instacart · Consumer · United States · Remote · Commercial Excellence

Instacart is seeking an Ads AI Analyst to own the intelligence behind their Ads agents. The role involves defining the Ads semantic/context layer, building vertical AI agents to analyze campaigns and recommend actions, and partnering with various teams to ship production agents. Responsibilities include defining ontologies, building data models, ingesting and enriching content, designing RAG workflows, establishing evaluation suites, and running experiments to quantify impact. The role requires strong SQL, Python, dbt, Snowflake, and Ads analytics expertise, with a focus on shipping AI systems that drive business impact.

What you'd actually do

  1. Define Ads ontologies and metrics for campaigns, budgets, bids, creatives, audiences, and placements.
  2. Build dbt models and curated marts in Snowflake with clear data contracts, tests, and SLOs.
  3. Ingest and enrich unstructured Ads content and publish retrieval‑ready datasets using our managed search/vector services.
  4. Design and evaluate retrieval workflows (RAG) with existing services for hybrid search and re‑ranking; set quality/latency targets and iterate via experiments.
  5. Design agent reasoning and policies on ads, including tool definitions and human‑in‑the‑loop approvals.

Skills

Required

  • 3–6 years in analytics engineering, data science, or applied AI with strong SQL and Python.
  • 2+ years of domain expertise in ads, retail, or e-commerce data.
  • Advanced Proficiency in Python and SQL, with experience using dbt and Snowflake or BigQuery, including skills in data modeling, testing, and managing data contracts.
  • Deep Expertise in orchestrating data pipelines using dbt and Airflow
  • Experience with at least one data visualization tool (Tableau, Mode, Power BI, Looker, or similar)
  • Ability to design offline/online evaluations and run A/B or uplift tests
  • Fluency in Ads analytics concepts such as ROAS, CPA, CTR, CVR, LTV, pacing, auction dynamics, and incrementality.
  • Strong stakeholder communication with a track record of shipping production data or AI systems that drove business impact.
  • Understanding of ML models to drive recommendations on bid, keywords, and budgets
  • Experience with evaluation and guardrail frameworks and human‑in‑the‑loop QA.

Nice to have

  • Strong understanding of AI and machine learning concepts, with experience creating AI-driven products.
  • Deep expertise in advertising products, including leading and driving automation projects.
  • Proven ability to improve operational efficiency through automation initiatives in fast-paced environments.
  • Applied experience in modeling techniques for Ads, including forecasting, anomaly detection, uplift modeling, and causal inference.
  • Hands-on experience with workflow automation and low-code development platforms (Zapier, n8n, Gumloop, Superblocks)
  • Familiarity with retail media or ad platforms, including Amazon, Google, Meta, Shopify, or DoorDash.

What the JD emphasized

  • shipping production agents with measurable lift
  • shipping production data or AI systems that drove business impact
  • evaluation and guardrail frameworks and human‑in‑the‑loop QA

Other signals

  • Build vertical AI agents that analyze campaigns, diagnose performance, and recommend actions
  • Design agent reasoning and policies on ads
  • Establish evaluation suites covering precision/recall, calibration, hallucination rate, latency, and cost
  • Translate Ads problems into agent behaviors and own KPIs such as ROAS lift, pacing accuracy, RCA precision/recall, forecast MAPE, and time-to-insight