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AirOps is a full-service platform helping brands achieve visibility and growth in the age of AI search. As consumers shift from traditional search engines to AI platforms like ChatGPT, Claude, and Gemini, the rules of discovery and purchasing are being rewritten. AirOps works with category leaders including Ramp, Chime, Airbnb, ServiceNow, and Rippling to ensure brands are found, recommended, and trusted by AI agents.
As Senior AI Data Analyst, you will be a hands-on individual contributor reporting to the Analytics Lead. You will build and expand AirOps' AI data stack by designing reliable data models that transform raw data into trusted analytical datasets. You will own metric definitions and data quality, ensuring models are tested, documented, and consistent across dashboards and AI tooling.
Your responsibilities include leading deep-dive analyses across Product, Finance, and GTM teams to identify optimization opportunities and provide clear recommendations. You will build dashboards and compelling visualizations for C-level and VP-level leaders. You will partner with the CX team to present insights directly to customers, connecting their GA4, Google Search Console, and AI Search data to business outcomes. You will also transform recurring internal and customer questions into reusable models, self-service resources, and reporting frameworks that scale.
The role offers potential to take on team leadership as the analytics function grows, with the company scaling toward $100M and beyond. You will use AI tools to accelerate work across all three areas: data modeling, business analysis, and customer insights.
Company is backed by Greylock, Unusual Ventures, Wing VC, and Founder Collective, with headquarters in San Francisco, New York, and Montevideo.
REQUIREMENTS:
- 5+ years in analytics or analytics engineering, including experience at rapidly growing startups
- Strong SQL skills: built data models from scratch, understand table relationships and grain, familiar with cloud data warehouses, can independently explain and debug logic
- AI-native: use tools like Claude Code and Codex to accelerate modeling and analysis, validate outputs against source data and business definitions
- Highly analytical: use cohort, funnel, and segmentation analysis to uncover insights and distinguish meaningful changes from noise
- Strong communicator: tell compelling data stories and make complex findings clear to executives, customers, and technical peers
- Thrive in ambiguity: clarify open-ended questions, prioritize by business impact, adapt quickly when needs change
- Hands-on owner: drive work from raw data to recommendations, follow through across technical, business, and customer contexts
- Quality-minded: move fast, validate results, communicate uncertainty, handle customer and business data responsibly
NICE TO HAVE:
- Customer-facing analytics experience
- Experience with GA4 and Google Search Console
- Familiarity with Metabase, dbt, semantic layers (Cube), and analytics delivered through MCP-connected AI tools
- Experience with AI search measurement, brand visibility, mention rates, and citation analysis
- Python proficiency for analysis, data validation, scripting, or automation
