Senior AI Data Analyst
Airops · New York City or San Francisco (Onsite)
About this role
## About AirOps AirOps is the full-service platform for brand growth in the age of AI search. As consumers shift from traditional search engines to platforms like ChatGPT, Claude, and Gemini, the rules of growth are changing—buyers now rely on agents to discover, recommend, and purchase products and services. If your brand isn’t part of the answer, you’re not in the running. AirOps helps brands get found, recommended, and earn trust, working with category leaders including teams at Ramp, Chime, Airbnb, ServiceNow, and Rippling. Backed by Greylock, Unusual Ventures, Wing VC, and Founder Collective, AirOps is headquartered in San Francisco, New York, and Montevideo. ## Role: Senior AI Data Analyst As a **Senior AI Data Analyst**, you’ll build trusted data models, drive business decisions, and help customers measure the value AirOps delivers. You’ll report to the **Analytics Lead** as a hands-on individual contributor, using AI to accelerate work across analytics, modeling, and insights. ## What You’ll Do - Expand the AI data stack by designing and building reliable data models that turn raw data into trusted analytical datasets. - Own metric definitions and data quality—keep models tested, documented, and consistent across dashboards and AI tooling. - Use AI to lead deep-dive analyses across **Product, Finance, and GTM** to identify opportunities and provide clear recommendations. - Build dashboards and compelling visualizations for C-level and VP-level leaders. - Partner with the CX team to present insights and actionable recommendations directly to customers, connecting **GA4, GSC, and AI Search** data to business outcomes. - Turn recurring internal and customer questions into reusable models, self-service resources, and scalable reporting frameworks. ## Who You Are - **5+ years** in analytics or analytics engineering, including experience at rapidly growing startups. - Strong **SQL** skills: you’ve built data models from scratch, understand table relationships/grain/warehouses, and can independently explain and debug your logic. - **AI-native**: you use tools like Claude Code and Codex to accelerate modeling and analysis, validating outputs against source data and business definitions. - Highly analytical: you use cohort, funnel, and segmentation analysis to uncover insights and separate signal from noise. - Strong communicator: you can tell compelling data stories and make complex findings clear to executives, customers, and technical peers. - Thrive in ambiguity: you clarify open-ended questions, prioritize by business impact, and adapt quickly. - Hands-on owner: you drive work from raw data to recommendations and follow through across technical, business, and customer contexts. - Quality-minded: you move fast, validate results, communicate uncertainty, and handle customer/business data responsibly. ## Nice to Have - Customer-facing analytics experience (presenting findings directly to customers). - Experience with **GA4** and **Google Search Console** (search, traffic, conversion analysis). - Familiarity with **Metabase**, **dbt**, semantic layers (Cube), and analytics delivered through **MCP-connected AI tools**. - Experience with AI search measurement (brand visibility, mention rates, citation analysis). - **Python** proficiency for analysis, data validation, scripting, or automation. ## Guiding Principles 1. Extreme Ownership 2. Quality 3. Curiosity and Play 4. Make Our Customers Heroes 5. Respectful Candor ## Benefits - E
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