Ads AI Analytics Lead

🕒 Junho 8

🏄 California, Colorado, +17 estados a mais – Remoto

🏄 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

💵 $131.000 - $165.000 / ano

⏰ Tempo Integral

🟠 Sênior

📊 Cientista de Dados

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Instacart

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 2012

🛍️ Comércio Eletrônico

🚗 Transporte

🛒 Varejo

💰 $232.000.000 Venture Round em 2021-11

eCommerce • Transport • Retail

A Instacart é uma empresa que oferece uma abordagem flexível de trabalho enquanto transforma o setor de supermercados. Ela presta um serviço essencial ao entregar compras de supermercado e itens para a casa na porta dos clientes em até 30 minutos. A Instacart oferece oportunidades de ganho seguras e flexíveis para personal shoppers e enfrenta desafios como redirecionar entregas durante nevascas e conectar clientes a cupons e promoções. Seu objetivo é ser o sistema operacional do setor de supermercados, ajudando os clientes a economizar tempo para outras atividades. A Instacart valoriza diversidade, equidade e pertencimento em sua cultura de trabalho.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

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