- Страна
- США
- Зарплата
- 157 000 $ – 165 000 $
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Ads AI Analytics Lead II
Отличная вакансия в топовой компании с прозрачной вилкой зарплаты, удаленным форматом работы и возможностью работать на острие технологий (AI Agents + AdTech).
Сложность вакансии
Высокая сложность обусловлена необходимостью сочетать глубокие знания в Analytics Engineering (dbt, Snowflake) с современными практиками AI (RAG, LLM agents) и специфической экспертизой в AdTech.
Анализ зарплаты
Предложенная зарплата ($157k - $165k для ключевых штатов) полностью соответствует рыночным ожиданиям для позиции Lead уровня в США, учитывая дополнительные бонусы в виде опционов.
Сопроводительное письмо
I am writing to express my strong interest in the Ads AI Analytics Lead II position at Instacart. With over 5 years of experience in analytics engineering and a deep focus on the advertising domain, I have consistently delivered data-driven solutions that optimize commercial performance. My background in building robust dbt models within Snowflake environments, combined with a practical understanding of RAG workflows and AI agent orchestration, aligns perfectly with the goals of the Commercial Scaled Intelligence team.
In my previous roles, I have successfully translated complex advertising challenges—such as ROAS optimization and pacing accuracy—into scalable automated systems. I am particularly drawn to Instacart's 'Flex First' approach and the opportunity to design the semantic layer for vertical AI agents. I am confident that my expertise in causal inference, A/B testing, and LLM evaluation frameworks will allow me to contribute immediately to driving measurable lift for your advertising partners.
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Откликнитесь в instacart уже сейчас
Присоединяйтесь к Instacart, чтобы создавать будущее рекламных AI-агентов и трансформировать индустрию ритейл-медиа!
Описание вакансии
We're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
Overview
The Commercial Scaled Intelligence (CSI) team is an AI-first team dedicated to delivering actionable commercial insights and scalable automation to drive revenue growth and operational efficiency across the company. The team focuses on intelligence generation, predictive analytics, and workflow automation to enable data-driven decision-making and optimize commercial performance.
As an Ads AI Analytics Lead II, you will own the intelligence behind our Ads agents. You will design the Ads semantic/context layer and build vertical AI agents that analyze campaigns, diagnose performance, and recommend actions that improve ROAS, pacing, and partner outcomes. You will partner with Ads GTM, Product, Data Science, and Engineering to ship production agents with measurable lift.
About the Job
- 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.
About You
Minimum Qualifications
- 4–7 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.
Preferred Qualifications
- 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.
#LI-Remote
Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.
Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.
For US based candidates, the base pay ranges for a successful candidate are listed below.
CA, NY, CT, NJ
$157,000—$165,000 USD
WA
$150,000—$159,000 USD
OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI
$144,000—$152,000 USD
All other states
$131,000—$138,000 USD
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Навыки
- SQL
- Python
- dbt
- Snowflake
- Airflow
- Tableau
- Looker
- RAG
- A/B Testing
- Machine Learning
- Causal Inference
- BigQuery
Возможные вопросы на собеседовании
Проверка понимания специфики рекламных метрик и их взаимосвязи.
Как бы вы спроектировали систему метрик для оценки инкрементальности (incrementality) рекламных кампаний в рамках AI-агента?
Оценка технических навыков в области RAG и работы с данными.
Опишите ваш подход к созданию и оценке качества поискового слоя (retrieval layer) для рекламных контекстных данных.
Проверка опыта работы с современным стеком аналитики.
Какие стратегии тестирования и обеспечения контрактов данных вы считаете наиболее эффективными при работе с dbt и Snowflake в высоконагруженных системах?
Оценка способности решать бизнес-задачи через AI.
Как минимизировать уровень галлюцинаций AI-агента при генерации рекомендаций по изменению ставок и бюджетов?
Проверка навыков проведения экспериментов.
Расскажите о самом сложном A/B тесте, который вы проводили для рекламного продукта: какие были гипотезы и как вы интерпретировали результаты?
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- Страна
- США
- Зарплата
- 157 000 $ – 165 000 $