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Senior AI Data Analyst

New York City or San Francisco (Onsite) · San Francisco, CA, United States

Pay
Pay not listedSimilar roles state $94K–$143K
Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Operations — team source
Department: Operations
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
For US-based applications: Do you now or will you in the future require visa sponsorship to work in the United States?
From the employer’s application form
Apply at AirOps

What you’ll work on

Full posting
  • Design and build reliable data models that turn raw data into trusted datasets

  • Own metric definitions and data quality across dashboards and AI tooling

  • Lead deep-dive analyses across Product, Finance, and GTM with clear recommendations

  • Build dashboards and visualizations to present findings to C-level and VP leaders

  • Present customer insights with the CX team, linking GA4, GSC, and AI Search data to outcomes

From the employer’s posting
designing and building reliable data models that turn raw data into trusted analytical datasets
Own metric definitions and data quality
Leverage AI to lead deep-dive analyses across Product, Finance, and GTM teams
Build dashboards and compelling visualizations to help communicate findings to C-level and VP-level leaders
Partner with our CX team to present insights and actionable recommendations directly to customers

What you’ll bring

All qualifications

Core experience

  • 5+ years in analytics or analytics engineering, including experience at rapidly growing startups.
  • Experience with GA4 and Google Search Console, including search, traffic, and conversion analysis.
  • Strong SQL skills — you’ve built data models from scratch, understand table relationships, grain, and cloud data warehouses, and can independently explain and debug your logic.
  • 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.
Qualification wording
5+ years in analytics or analytics engineering, including experience at rapidly growing startups.
Experience with GA4 and Google Search Console, including search, traffic, and conversion analysis.
Strong SQL skills — you’ve built data models from scratch, understand table relationships, grain, and cloud data warehouses, and can independently explain and debug your logic.
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.

Tools in this posting

  • Python
  • SQL
  • dbt
  • Metabase
Source — Tool mentions in context
- Experience with AI search measurement, brand visibility, mention rates, and citation analysis. - Python proficiency for analysis, data validation, scripting, or automation. Our Guiding Principles
- 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, and cloud data warehouses, and can independently explain and debug your logic. - AI-native — you use tools like Claude Code and Codex to accelerate modeling and analysis, and validate outputs against source data and business definitions.
- Experience with GA4 and Google Search Console, including search, traffic, and 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, and citation analysis.

Benefits in the posting

Full benefits wording
  • Equity in a fast-growing startup
  • Competitive benefits package tailored to your location
  • Flexible time off policy
  • Parental Leave

From the employer’s posting.

About AirOps

AirOps is the full-service platform for brand growth in the age of AI search.

In the employer’s words · Read in context · Company website ↗

Posting record

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Status in our records
Live
First seen by us
Oct 15, 2026 · 14 days ago
Recorded sightings
15
Last seen by us
Oct 29, 2026

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Job description

View original posting ↗

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 entire ruleset of growth is being rewritten. Buyers now rely on agents to discover, recommend, and purchase products and services for them. If your brand isn't part of the answer, you aren't in the running.

Our platform offers everything a brand needs to get found, recommended, and earn trust. We work with category leaders, including teams at Ramp, Chime, Airbnb, ServiceNow, and Rippling, to drive visibility and accelerate growth from AI search.

Backed by Greylock, Unusual Ventures, Wing VC, and Founder Collective, we're headquartered in San Francisco, New York, and Montevideo.

As our Senior AI Analyst, you’ll build trusted data models, drive business decisions, and help customers measure the value AirOps delivers. You’ll report to our Analytics Lead as a hands-on individual contributor, using AI to accelerate work across all three areas. Priorities will evolve as AirOps continues to scale to $100M and beyond, with potential to take on team leadership as the analytics function grows.

What you’ll do
  • Expand our current 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.

  • Leverage AI to lead deep-dive analyses across Product, Finance, and GTM teams to identify opportunities and provide clear recommendations on ways to optimize the business.

  • Build dashboards and compelling visualizations to help communicate findings to C-level and VP-level leaders.

  • Partner with our CX team to present insights and actionable recommendations directly to customers, connecting their GA4, GSC, and AI Search data to business outcomes.

  • Turn recurring internal and customer questions into reusable models, self-service resources, and reporting frameworks that scale.

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, and cloud data warehouses, and can independently explain and debug your logic.

  • AI-native — you use tools like Claude Code and Codex to accelerate modeling and analysis, and validate outputs against source data and business definitions.

  • Highly analytical — you use cohort, funnel, and segmentation analysis to uncover insights and distinguish meaningful changes from noise.

  • Strong communicator — you 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 when needs change.

  • 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 and business data responsibly.

Nice to have
  • Customer-facing analytics experience — you’ve led discussions and presented findings directly to customers.

  • Experience with GA4 and Google Search Console, including search, traffic, and 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, and citation analysis.

  • Python proficiency for analysis, data validation, scripting, or automation.

Our Guiding Principles

  1. Extreme Ownership

  2. Quality

  3. Curiosity and Play

  4. Make Our Customers Heroes

  5. Respectful Candor

Benefits

  • Equity in a fast-growing startup

  • Competitive benefits package tailored to your location

  • Flexible time off policy

  • Parental Leave

  • A fun-loving and (just a bit) nerdy team that loves to move fast!

Source details

View original posting ↗

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Location & working pattern

San Francisco, CA, United States

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