Ads AI Analytics Lead

🕒 June 8

🏄 California, Colorado, +17 more states – Remote

🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🌺 Hawaii – Remote 🌽 Illinois – Remote 🦞 Maine – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🤠 Texas – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote

💵 $131k - $165k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Instacart

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2012

🛍️ eCommerce

🚗 Transport

🛒 Retail

💰 $232M Venture Round on 2021-11

eCommerce • Transport • Retail

Instacart is a company that offers a flexible approach to work while transforming the grocery industry. It provides an essential service by delivering groceries and household goods to customers' doors in as little as 30 minutes. Instacart offers safe and flexible earning opportunities to personal shoppers and tackles challenges such as rerouting deliveries during snowstorms and connecting customers with coupons and deals. It aims to be the operating system for the grocery industry, thus helping customers save time for other activities. Instacart emphasizes diversity, equity, and belonging in its work culture.

📋 Description

• 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

• 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

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