Senior AI Data Analyst
Join AirOps as a Senior AI Data Analyst to build data models and drive business decisions in a fast-growing startup.
Posted by employer 13 hours ago
First seen on Joblaze 9 hours ago
Last verified on the company career page 9 hours ago
Skills & Technologies
What you'll build
- Design and build reliable data models
- Own metric definitions and data quality
- Lead deep-dive analyses across teams
- Build dashboards and visualizations
- Present insights and recommendations to customers
Must have
- 5+ years in analytics or analytics engineering
- Strong SQL skills
- AI-native experience
- Highly analytical
- Strong communicator
- Hands-on owner
Nice to have
- Customer-facing analytics experience
- Experience with GA4 and Google Search Console
- Familiarity with Metabase and dbt
- Experience with AI search measurement
- Python proficiency
AI in the day-to-day
Use AI to accelerate work across analytics and drive business decisions.
Requirements
- Experience
- 5+ years
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
In the role of Senior AI Data Analyst at AirOps, the individual will focus on developing and refining data models to transform raw data into actionable insights that drive business decisions. Proficiency in SQL and familiarity with AI tools are essential, as the analyst will leverage these skills to conduct in-depth analyses across various teams and create visualizations for executive-level communication. This position is ideal for someone with over five years of experience in analytics, particularly in fast-paced startup environments, who thrives in ambiguity and values data quality.
Joblaze insights
Quick facts
- Is the Senior AI Data Analyst role remote?
- No — this is an on-site role in San Francisco, United States.
- How much experience is required?
- At least 5 years of relevant experience for this Senior AI Data Analyst role.
- Where is the role based?
- AirOps is hiring for this position in San Francisco, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI, GA4, Google Search Console, Python, SQL.
- What seniority level is this role?
- AirOps targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Senior AI Data Analyst role at AirOps.
From the original posting
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
Extreme Ownership
Quality
Curiosity and Play
Make Our Customers Heroes
Respectful Candor
Benefits
Equity in a fast-growing startup
Competitive benefits package tailored to your location
Flexible time off policy
Parental Leave
Standard company text repeated across AirOps's postings is omitted here.