Ads AI Analytics Lead

Instacart

Ads AI Analytics Lead II optimizing ads performance and delivering insights for Instacart's AI-first team. Collaborating across product, data science, and engineering to improve revenue growth.

Posted 6/8/2026full-timeRemote • California, Colorado, Connecticut, District of Columbia, Hawaii, Illinois, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Oregon, Pennsylvania, Rhode Island, Texas, Vermont, Virginia, Washington • 🇺🇸 United StatesSenior💰 $131,000 - $165,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowBigQueryPythonSQLTableau

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Competitive salary
New hire equity grant
Annual refresh grants
Flexible work arrangements

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPythondbtSnowflakeBigQuerydata modelingdata testingdata pipeline orchestrationA/B testingevaluation frameworks

Soft Skills

stakeholder communicationproblem translationiteration guidancedata-driven decision making